DSC8 Independent project R
ROY MWANGI
5/19/2021
1.0 Defining the Question
A Kenyan entrepreneur has created an online cryptography course and would want to advertise it on her blog. She currently targets audiences originating from various countries. In the past, she ran ads to advertise a related course on the same blog and collected data in the process. She would now like to employ your services as a Data Science Consultant to help her identify which individuals are most likely to click on her ads.
Data provided
Dataset Url = http://bit.ly/IPAdvertisingData
Data grossary
Age
Daily Time spent on site
Area of residence
Internet Usage
Gender
Country of residence
1.1 Specifying the data analytic
To find out individuals that are likely to click on a blog advert based on their characteristics
1.2 Defining the metric for success
Identify individuals that are likely to click on the add after performing exploratory data analysis
1.3 Understanding the Context
A Kenyan entrepreneur has created an online cryptography course and would want to advertise it on her blog. She currently targets audiences originating from various countries. In the past, she ran ads to advertise a related course on the same blog and collected data in the process.
1.4 Recording the Experimental
1.Data Loading
2.Data cleaning for missing values and outliers
3.Exploratory Data Analysis
4.Conclusion-Detecting the trend in behavior.
1.5 Assessing the Relevance of the Data
The data provided is from the performance of a previous blog advert on the same website. The columns are as follows: Daily Time Spent on the site-Integer, Age-Age of the individual browsing-Integer, Area of residence Internet Usage Gender of the browsing individual Country of Residence
2.0 Importing package
#loading the library
library(data.table) # load package
#to work with data frame - extends into visualization
library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.2 v dplyr 1.0.6
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::between() masks data.table::between()
## x dplyr::filter() masks stats::filter()
## x dplyr::first() masks data.table::first()
## x dplyr::lag() masks stats::lag()
## x dplyr::last() masks data.table::last()
## x purrr::transpose() masks data.table::transpose()observation; This library package installation help us to work with tables and dataframe respectively.
##2.1 Importing dataset
# Dataset Url = http://bit.ly/IPAdvertisingData
# Importing our dataset
# ---
#
advertising_dataset <- read.csv('http://bit.ly/IPAdvertisingData')
# Previewing the dataset
# ---
#having a look at the dataset
head(advertising_dataset, 6)## Daily.Time.Spent.on.Site Age Area.Income Daily.Internet.Usage
## 1 68.95 35 61833.90 256.09
## 2 80.23 31 68441.85 193.77
## 3 69.47 26 59785.94 236.50
## 4 74.15 29 54806.18 245.89
## 5 68.37 35 73889.99 225.58
## 6 59.99 23 59761.56 226.74
## Ad.Topic.Line City Male Country
## 1 Cloned 5thgeneration orchestration Wrightburgh 0 Tunisia
## 2 Monitored national standardization West Jodi 1 Nauru
## 3 Organic bottom-line service-desk Davidton 0 San Marino
## 4 Triple-buffered reciprocal time-frame West Terrifurt 1 Italy
## 5 Robust logistical utilization South Manuel 0 Iceland
## 6 Sharable client-driven software Jamieberg 1 Norway
## Timestamp Clicked.on.Ad
## 1 2016-03-27 00:53:11 0
## 2 2016-04-04 01:39:02 0
## 3 2016-03-13 20:35:42 0
## 4 2016-01-10 02:31:19 0
## 5 2016-06-03 03:36:18 0
## 6 2016-05-19 14:30:17 0observation: the dateset has 10 columns.
Previewing the dataset
#viewing the dataset
#
View(advertising_dataset)observation: the dataset has 100 records and 10 variables/columns.
checking the colunms summary
# checking the content/summary statistics of each column.
str(advertising_dataset)## 'data.frame': 1000 obs. of 10 variables:
## $ Daily.Time.Spent.on.Site: num 69 80.2 69.5 74.2 68.4 ...
## $ Age : int 35 31 26 29 35 23 33 48 30 20 ...
## $ Area.Income : num 61834 68442 59786 54806 73890 ...
## $ Daily.Internet.Usage : num 256 194 236 246 226 ...
## $ Ad.Topic.Line : chr "Cloned 5thgeneration orchestration" "Monitored national standardization" "Organic bottom-line service-desk" "Triple-buffered reciprocal time-frame" ...
## $ City : chr "Wrightburgh" "West Jodi" "Davidton" "West Terrifurt" ...
## $ Male : int 0 1 0 1 0 1 0 1 1 1 ...
## $ Country : chr "Tunisia" "Nauru" "San Marino" "Italy" ...
## $ Timestamp : chr "2016-03-27 00:53:11" "2016-04-04 01:39:02" "2016-03-13 20:35:42" "2016-01-10 02:31:19" ...
## $ Clicked.on.Ad : int 0 0 0 0 0 0 0 1 0 0 ...observation: the columns comprises of numerical, integer, and character data types.
checking the dataset dimension.
# dimension
dim(advertising_dataset)## [1] 1000 10observation: there is 1000 columns and 10 rows
checking our dataset class
class(advertising_dataset)## [1] "data.frame"converting the data into a tibble for easy manupulation
library(tibble)#For ease in analysis,we convert the data into a tibble
my_dataset<-as_tibble(advertising_dataset) # there is suggestion to use as_tibble instead of as.tibble.
head(my_dataset)## # A tibble: 6 x 10
## Daily.Time.Spent~ Age Area.Income Daily.Internet.~ Ad.Topic.Line City Male
## <dbl> <int> <dbl> <dbl> <chr> <chr> <int>
## 1 69.0 35 61834. 256. Cloned 5thge~ Wrig~ 0
## 2 80.2 31 68442. 194. Monitored na~ West~ 1
## 3 69.5 26 59786. 236. Organic bott~ Davi~ 0
## 4 74.2 29 54806. 246. Triple-buffe~ West~ 1
## 5 68.4 35 73890. 226. Robust logis~ Sout~ 0
## 6 60.0 23 59762. 227. Sharable cli~ Jami~ 1
## # ... with 3 more variables: Country <chr>, Timestamp <chr>,
## # Clicked.on.Ad <int>Explanation: converting to tibble makes it easy for manipulation.
dataset summary
summary(my_dataset)## Daily.Time.Spent.on.Site Age Area.Income Daily.Internet.Usage
## Min. :32.60 Min. :19.00 Min. :13996 Min. :104.8
## 1st Qu.:51.36 1st Qu.:29.00 1st Qu.:47032 1st Qu.:138.8
## Median :68.22 Median :35.00 Median :57012 Median :183.1
## Mean :65.00 Mean :36.01 Mean :55000 Mean :180.0
## 3rd Qu.:78.55 3rd Qu.:42.00 3rd Qu.:65471 3rd Qu.:218.8
## Max. :91.43 Max. :61.00 Max. :79485 Max. :270.0
## Ad.Topic.Line City Male Country
## Length:1000 Length:1000 Min. :0.000 Length:1000
## Class :character Class :character 1st Qu.:0.000 Class :character
## Mode :character Mode :character Median :0.000 Mode :character
## Mean :0.481
## 3rd Qu.:1.000
## Max. :1.000
## Timestamp Clicked.on.Ad
## Length:1000 Min. :0.0
## Class :character 1st Qu.:0.0
## Mode :character Median :0.5
## Mean :0.5
## 3rd Qu.:1.0
## Max. :1.0observation, we are able to get precise summary of all our dataset columns, this will be detailed in analysis section.However, we will still check for missing values
3.0 Data cleaning
###3.0a missing values
# Identify missing data in our entire dataset using is.na() function
#
is.na(my_dataset)## Daily.Time.Spent.on.Site Age Area.Income Daily.Internet.Usage
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## [1000,] FALSE FALSE FALSE FALSE FALSE FALSEobservation: there is no missing values as all the result returns False result.However, we will use another method to ascertain the above.
###3.0b Checking for missing values using the complete function
# using complete function
my_dataset[!complete.cases(my_dataset),]## # A tibble: 0 x 10
## # ... with 10 variables: Daily.Time.Spent.on.Site <dbl>, Age <int>,
## # Area.Income <dbl>, Daily.Internet.Usage <dbl>, Ad.Topic.Line <chr>,
## # City <chr>, Male <int>, Country <chr>, Timestamp <chr>, Clicked.on.Ad <int>observation: we got 0 row output, and all columns are complete hence no missing values.
###3.0c Finding out total missing values in each column
#Rechecking the sum of missing values to ascertain the above finding
#
colSums(is.na(my_dataset))## Daily.Time.Spent.on.Site Age Area.Income
## 0 0 0
## Daily.Internet.Usage Ad.Topic.Line City
## 0 0 0
## Male Country Timestamp
## 0 0 0
## Clicked.on.Ad
## 0observation: we can confirm there is no missing values in our dataset.
3.1a Duplicated Data
#Identifying Duplicated Data
#
duplicated_rows <- my_dataset[duplicated(my_dataset),]
duplicated_rows## # A tibble: 0 x 10
## # ... with 10 variables: Daily.Time.Spent.on.Site <dbl>, Age <int>,
## # Area.Income <dbl>, Daily.Internet.Usage <dbl>, Ad.Topic.Line <chr>,
## # City <chr>, Male <int>, Country <chr>, Timestamp <chr>, Clicked.on.Ad <int>observation, there is no duplicated rows
3.1b showing unique items
#showing these unique items
#
unique_items <- my_dataset[!duplicated(my_dataset), ]
unique_items## # A tibble: 1,000 x 10
## Daily.Time.Spen~ Age Area.Income Daily.Internet.~ Ad.Topic.Line City Male
## <dbl> <int> <dbl> <dbl> <chr> <chr> <int>
## 1 69.0 35 61834. 256. Cloned 5thge~ Wrig~ 0
## 2 80.2 31 68442. 194. Monitored na~ West~ 1
## 3 69.5 26 59786. 236. Organic bott~ Davi~ 0
## 4 74.2 29 54806. 246. Triple-buffe~ West~ 1
## 5 68.4 35 73890. 226. Robust logis~ Sout~ 0
## 6 60.0 23 59762. 227. Sharable cli~ Jami~ 1
## 7 88.9 33 53853. 208. Enhanced ded~ Bran~ 0
## 8 66 48 24593. 132. Reactive loc~ Port~ 1
## 9 74.5 30 68862 222. Configurable~ West~ 1
## 10 69.9 20 55642. 184. Mandatory ho~ Rami~ 1
## # ... with 990 more rows, and 3 more variables: Country <chr>, Timestamp <chr>,
## # Clicked.on.Ad <int>observation: these shows the unique items hence no duplicated rows.
###3.2 Outliers
installing outlier package and library
#
library(outliers)###3.2a Identifying the numeric class in the data and evaluating if there are any outliers
#Checking the data types of the columns
#
Numeric<- my_dataset %>% select_if(is.numeric)
Numeric## # A tibble: 1,000 x 6
## Daily.Time.Spent.on~ Age Area.Income Daily.Internet.Us~ Male Clicked.on.Ad
## <dbl> <int> <dbl> <dbl> <int> <int>
## 1 69.0 35 61834. 256. 0 0
## 2 80.2 31 68442. 194. 1 0
## 3 69.5 26 59786. 236. 0 0
## 4 74.2 29 54806. 246. 1 0
## 5 68.4 35 73890. 226. 0 0
## 6 60.0 23 59762. 227. 1 0
## 7 88.9 33 53853. 208. 0 0
## 8 66 48 24593. 132. 1 1
## 9 74.5 30 68862 222. 1 0
## 10 69.9 20 55642. 184. 1 0
## # ... with 990 more rowsobservation: these columns have numeric datatyp:Daily Time Spent on site,Age,Area,Income,Daily Internet Usage,gender and whether the individual clicked on the add
##3.2a Identifying the numeric class in the data
#Checking the data types of the columns
Categorical=my_dataset %>% select_if(is.character)
Categorical## # A tibble: 1,000 x 4
## Ad.Topic.Line City Country Timestamp
## <chr> <chr> <chr> <chr>
## 1 Cloned 5thgeneration orchestrati~ Wrightburgh Tunisia 2016-03-27 00:53~
## 2 Monitored national standardizati~ West Jodi Nauru 2016-04-04 01:39~
## 3 Organic bottom-line service-desk Davidton San Mari~ 2016-03-13 20:35~
## 4 Triple-buffered reciprocal time-~ West Terrifurt Italy 2016-01-10 02:31~
## 5 Robust logistical utilization South Manuel Iceland 2016-06-03 03:36~
## 6 Sharable client-driven software Jamieberg Norway 2016-05-19 14:30~
## 7 Enhanced dedicated support Brandonstad Myanmar 2016-01-28 20:59~
## 8 Reactive local challenge Port Jefferybu~ Australia 2016-03-07 01:40~
## 9 Configurable coherent function West Colin Grenada 2016-04-18 09:33~
## 10 Mandatory homogeneous architectu~ Ramirezton Ghana 2016-07-11 01:42~
## # ... with 990 more rowsobservation: these columns have character datatype:Ad topic line,City,Country and Timestamp
3.2b Checking for outliers
#checking outliers in numerical colunms
#
outlier(Numeric)## Daily.Time.Spent.on.Site Age Area.Income
## 32.60 61.00 13996.50
## Daily.Internet.Usage Male Clicked.on.Ad
## 269.96 1.00 1.00observation, there is outliers in all the numerical columns.However, we will check each column separately.
#3.2bi. Checking the outliers in the 'Daily.Time.Spent.on.Site' Column.
#
boxplot(my_dataset$Daily.Time.Spent.on.Site, main= "Daily.Time.Spent.on.Site boxplot",ylab="Daily.Time.Spent.on.Site", boxwex=0.2)
observation, there is no outlier in Daily.Time.Spent.on.Site colunm.
#3.2bii. Checking the outliers in the 'Age' Column using univariate approach
#
boxplot(my_dataset$Age, main="Age boxplot",ylab = "Age", boxwex=0.2)
observation, there is no outlier in Age column
#3.2biii. Checking the outliers in the 'Area.Income' Column using univariate approach
#
boxplot(my_dataset$Area.Income, main="Area.Income boxplot",ylab = "Area.Income", boxwex=0.2)
observation: using boxplot shows outliers, we will use ggplot2 for further analysis.
###3.3a installing the ggplot2 package and library
#3.3ai installing ggplot2 package for visualization.
install.packages('ggplot2')## Warning: package 'ggplot2' is in use and will not be installed#
#installing ggplot2 library
#
library(ggplot2)
#
#note: the above have been installed in the console section.#visualizing the colunm to check for outliers
ggplot2::qplot(data = my_dataset, x = Area.Income)## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#checking for outlier
outlier_value <-boxplot.stats(my_dataset$Area.Income)$out
outlier_value## [1] 17709.98 18819.34 15598.29 15879.10 14548.06 13996.50 14775.50 18368.57observation, there is outliers however this might be genuine thus we will not remove them since it is not extreme.
#3.2bii. Checking the outliers in the 'Daily.Internet.Usage' Column using univariate approach
#
boxplot(my_dataset$Daily.Internet.Usage, main="Daily.Internet.Usage boxplot",ylab = "Daily.Internet.Usage", boxwex=0.2)
observation, there is no outliers in Daily.Internet.Usage columns.
4.0 Univariate Analysis
4.1 univariate Analysis for Numerical Data
#previewing the data types of the columns
#
Numeric## # A tibble: 1,000 x 6
## Daily.Time.Spent.on~ Age Area.Income Daily.Internet.Us~ Male Clicked.on.Ad
## <dbl> <int> <dbl> <dbl> <int> <int>
## 1 69.0 35 61834. 256. 0 0
## 2 80.2 31 68442. 194. 1 0
## 3 69.5 26 59786. 236. 0 0
## 4 74.2 29 54806. 246. 1 0
## 5 68.4 35 73890. 226. 0 0
## 6 60.0 23 59762. 227. 1 0
## 7 88.9 33 53853. 208. 0 0
## 8 66 48 24593. 132. 1 1
## 9 74.5 30 68862 222. 1 0
## 10 69.9 20 55642. 184. 1 0
## # ... with 990 more rows###4.1a checking for measure of central tedency
we will compute mean, median,maximum, range, quantile, variance, std, & boxplots for each numeric column #
#4.1b central tedency for ‘Daily.Time.Spent.on.Site’ colunm
#Finding the mean
DTS_m<-mean(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_m)## [1] 65.0002#Finding the median
DTS_m1<-median(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_m1)## [1] 68.215#Finding the maximum value in the Daily Time Spent on Site column
DTS_Max<-max(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_Max)## [1] 91.43#Finding the minimum value in the Daily Time Spent on Site column
DTS_Min<-min(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_Min)## [1] 32.6#Finding the range value of the Daily Time Spent on Site column
DTS_Range<-range(advertising_dataset$Daily.Time.Spent.on.Site)
print(DTS_Range)## [1] 32.60 91.43#Finding the variance of the Daily Time Spent on Site column
DTS_Variance<-var(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_Variance)## [1] 251.3371#Finding the standard deviation of the Daily Time Spent on Site column
DTS_Sd<-sd(my_dataset$Daily.Time.Spent.on.Site)
print(DTS_Sd)## [1] 15.85361###4.1c creating mode() function.
# We create the mode function that will perform our mode operation for us
getmode <- function(v) {
uniqv <- unique(v)
uniqv[which.max(tabulate(match(v, uniqv)))]
}
#
#finding the mode
DTS.Mode<-getmode(my_dataset$Daily.Time.Spent.on.Site)
DTS.Mode## [1] 62.264.1d finding quantile for ‘Time.Spent.on.Site’ variable
DTS_quantile <- quantile(my_dataset$Daily.Time.Spent.on.Site)
DTS_quantile## 0% 25% 50% 75% 100%
## 32.6000 51.3600 68.2150 78.5475 91.43004.1e “Daily.Time.Spent.on.Site” variable histogram
#Checking the distribution of Daily Time Spent on Site
hist(my_dataset$Daily.Time.Spent.on.Site)
observation: 80 daily time spend on the side registered higher records.
note: boxplot was already plotted earlier while checking for outliers.
4.1c central tedency for Age colunm
#Finding the mean
Age_m<-mean(my_dataset$Age)
print(Age_m)## [1] 36.009#Finding the median
Age_m1<-median(my_dataset$Age)
print(Age_m1)## [1] 35#Finding the maximum value in the age column
Age_Max<-max(my_dataset$Age)
print(Age_Max)## [1] 61#Finding the minimum value in the age column
Age_Min<-min(my_dataset$Age)
print(Age_Min)## [1] 19#Finding the range value of the age column
Age_Range<-range(my_dataset$Age)
print(Age_Range)## [1] 19 61#Finding the variance of the age column
Age_Variance<-var(my_dataset$Age)
print(Age_Variance)## [1] 77.18611#Finding the standard deviation of the age column
Age_Sd<-sd(my_dataset$Age)
print(Age_Sd)## [1] 8.785562#finding the mode## mode function was created in the console section to avoid several installation.
Age_Mode<-getmode(my_dataset$Age)
Age_Mode## [1] 31#4.2d finding quantile for 'Age' variable
Age_Mode<-quantile(my_dataset$Age)
Age_Mode## 0% 25% 50% 75% 100%
## 19 29 35 42 61###4.2e “Age” variable histogram
#Checking the distribution of Age
hist(my_dataset$Age)
observation: 30 to 35 years registered high records.
note: boxplot was done under outlier checking.
4.3a central tedency for Area.Income colunm
#Finding the mean
AI_m<-mean(my_dataset$Area.Income)
print(AI_m)## [1] 55000#
#Finding the median
AI_m1<-median(my_dataset$Area.Income)
print(AI_m1)## [1] 57012.3#
#Finding the maximum value in the Area Income column
AI_Max<-max(my_dataset$Area.Income)
print(AI_Max)## [1] 79484.8#
#Finding the minimum value in the Area Income column
AI_Min<-min(my_dataset$Area.Income)
print(AI_Min)## [1] 13996.5#
#Finding the range value of the Area Income column
AI_Range<-range(my_dataset$Area.Income)
print(AI_Range)## [1] 13996.5 79484.8#
#Finding the variance of the Area Income column
AI_Variance<-var(my_dataset$Area.Income)
print(AI_Variance)## [1] 179952406#
#Finding the standard deviation of the Area Income column
AI_Sd<-sd(my_dataset$Area.Income)
print(AI_Sd)## [1] 13414.63#
#Finding the mode of the Area Income colunm
AI_Mode<-getmode(my_dataset$Area.Income)
print(AI_Mode)## [1] 61833.9#
#finding the quantile the Area Income colunm
AI_quantile<- quantile(my_dataset$Area.Income)
print(AI_quantile)## 0% 25% 50% 75% 100%
## 13996.50 47031.80 57012.30 65470.64 79484.80###4.3b “Area Income” variable histogram
#Checking the distribution of Area Income
hist(my_dataset$Area.Income)
observation: hire records were between 50000 and 70000 area income.
note: boxplot was used in outlier section.
4.4a central tedency for Daily.Internet.Usage colunm
#Finding the mean
DIU_m<-mean(my_dataset$Daily.Internet.Usage)
print(DIU_m)## [1] 180.0001#Finding the median
DIU_m1<-median(my_dataset$Daily.Internet.Usage)
print(DIU_m1)## [1] 183.13#Finding the maximum value in the Daily Internet Usage column
DIU_Max<-max(my_dataset$Daily.Internet.Usage)
print(DIU_Max)## [1] 269.96#Finding the minimum value in the Daily Internet Usage column
DIU_Min<-min(my_dataset$Daily.Internet.Usage)
print(DIU_Min)## [1] 104.78#Finding the range value of the Daily Internet Usagecolumn
DIU_Range<-range(my_dataset$Daily.Internet.Usage)
print(DIU_Range)## [1] 104.78 269.96#Finding the variance of the Daily Internet Usage column
DIU_Variance<-var(my_dataset$Daily.Internet.Usage)
print(DIU_Variance)## [1] 1927.415#Finding the standard deviation Daily Internet Usage column
DIU_Sd<-sd(my_dataset$Daily.Internet.Usage)
print(DIU_Sd)## [1] 43.90234#Finding the mode of the Daily internet usage colunm
DIU_Mode<-getmode(my_dataset$Daily.Internet.Usage)
print(DIU_Mode)## [1] 167.22#
#finding the quantile the Daily internet usage colunm
DIU_quantile<- quantile(my_dataset$Daily.Internet.Usage)
print(DIU_quantile)## 0% 25% 50% 75% 100%
## 104.7800 138.8300 183.1300 218.7925 269.9600###4.3b “Daily.Internet.Usage” variable histogram
#Checking the distribution of Daily internet Usage
hist(my_dataset$Daily.Internet.Usage)
observation: high records were witnessed at 125mbs and 225mbs daily internet usage.
Note: despite Male, and Clicked.on.Ad variables are categorical despite being under numerical datatypes.
4.5 summary statistics of the numerical variables
#Getting the summary statistics of the numeric variables.
summary(Numeric)## Daily.Time.Spent.on.Site Age Area.Income Daily.Internet.Usage
## Min. :32.60 Min. :19.00 Min. :13996 Min. :104.8
## 1st Qu.:51.36 1st Qu.:29.00 1st Qu.:47032 1st Qu.:138.8
## Median :68.22 Median :35.00 Median :57012 Median :183.1
## Mean :65.00 Mean :36.01 Mean :55000 Mean :180.0
## 3rd Qu.:78.55 3rd Qu.:42.00 3rd Qu.:65471 3rd Qu.:218.8
## Max. :91.43 Max. :61.00 Max. :79485 Max. :270.0
## Male Clicked.on.Ad
## Min. :0.000 Min. :0.0
## 1st Qu.:0.000 1st Qu.:0.0
## Median :0.000 Median :0.5
## Mean :0.481 Mean :0.5
## 3rd Qu.:1.000 3rd Qu.:1.0
## Max. :1.000 Max. :1.05.0 univariate Analysis for categorical Variable
#Checking the data types of the categorical columns
Categorical=my_dataset %>% select_if(is.character)
Categorical## # A tibble: 1,000 x 4
## Ad.Topic.Line City Country Timestamp
## <chr> <chr> <chr> <chr>
## 1 Cloned 5thgeneration orchestrati~ Wrightburgh Tunisia 2016-03-27 00:53~
## 2 Monitored national standardizati~ West Jodi Nauru 2016-04-04 01:39~
## 3 Organic bottom-line service-desk Davidton San Mari~ 2016-03-13 20:35~
## 4 Triple-buffered reciprocal time-~ West Terrifurt Italy 2016-01-10 02:31~
## 5 Robust logistical utilization South Manuel Iceland 2016-06-03 03:36~
## 6 Sharable client-driven software Jamieberg Norway 2016-05-19 14:30~
## 7 Enhanced dedicated support Brandonstad Myanmar 2016-01-28 20:59~
## 8 Reactive local challenge Port Jefferybu~ Australia 2016-03-07 01:40~
## 9 Configurable coherent function West Colin Grenada 2016-04-18 09:33~
## 10 Mandatory homogeneous architectu~ Ramirezton Ghana 2016-07-11 01:42~
## # ... with 990 more rows###5.1a “Male” variable frequencty barplot
Gender <- my_dataset$Male
Gender_frequency<- table(Gender)
Gender_frequency## Gender
## 0 1
## 519 481barplot(Gender_frequency,xlab ="gender", ylab = "browsing individuals", col="beige")
observation: Out of the 1,000 browsing individuals,519 were female whereas 481 were male
###5.1b “Clicked.on.Ad” variable frequencty barplot
Clicked <- my_dataset$Clicked.on.Ad
Clicked_frequency<- table(Clicked)
Clicked_frequency## Clicked
## 0 1
## 500 500barplot(Clicked_frequency,xlab ="Clicked.on.Ad", ylab = "clicking individuals", col="brown")
observation: Out of the 1,000 browsing individuals,500 people clicked on the advert whereas an equal number did not click the ad.
###5.1c “Country” variable frequencty barplot
Country <- my_dataset$Country
Country_frequency<- table(Country)
Country_frequency## Country
## Afghanistan
## 8
## Albania
## 7
## Algeria
## 6
## American Samoa
## 5
## Andorra
## 2
## Angola
## 4
## Anguilla
## 6
## Antarctica (the territory South of 60 deg S)
## 3
## Antigua and Barbuda
## 5
## Argentina
## 2
## Armenia
## 3
## Aruba
## 1
## Australia
## 8
## Austria
## 5
## Azerbaijan
## 3
## Bahamas
## 7
## Bahrain
## 5
## Bangladesh
## 4
## Barbados
## 5
## Belarus
## 6
## Belgium
## 5
## Belize
## 5
## Benin
## 2
## Bermuda
## 1
## Bhutan
## 2
## Bolivia
## 6
## Bosnia and Herzegovina
## 7
## Bouvet Island (Bouvetoya)
## 5
## Brazil
## 5
## British Indian Ocean Territory (Chagos Archipelago)
## 1
## British Virgin Islands
## 3
## Brunei Darussalam
## 5
## Bulgaria
## 6
## Burkina Faso
## 4
## Burundi
## 7
## Cambodia
## 7
## Cameroon
## 5
## Canada
## 5
## Cape Verde
## 1
## Cayman Islands
## 5
## Central African Republic
## 2
## Chad
## 4
## Chile
## 4
## China
## 6
## Christmas Island
## 6
## Colombia
## 2
## Comoros
## 2
## Congo
## 4
## Cook Islands
## 3
## Costa Rica
## 6
## Cote d'Ivoire
## 4
## Croatia
## 6
## Cuba
## 5
## Cyprus
## 8
## Czech Republic
## 9
## Denmark
## 3
## Djibouti
## 2
## Dominica
## 5
## Dominican Republic
## 4
## Ecuador
## 5
## Egypt
## 5
## El Salvador
## 6
## Equatorial Guinea
## 4
## Eritrea
## 7
## Estonia
## 3
## Ethiopia
## 7
## Falkland Islands (Malvinas)
## 4
## Faroe Islands
## 3
## Fiji
## 7
## Finland
## 5
## France
## 9
## French Guiana
## 4
## French Polynesia
## 5
## French Southern Territories
## 5
## Gabon
## 6
## Gambia
## 2
## Georgia
## 4
## Germany
## 1
## Ghana
## 4
## Gibraltar
## 3
## Greece
## 8
## Greenland
## 5
## Grenada
## 4
## Guadeloupe
## 2
## Guam
## 4
## Guatemala
## 4
## Guernsey
## 3
## Guinea
## 3
## Guinea-Bissau
## 2
## Guyana
## 5
## Haiti
## 2
## Heard Island and McDonald Islands
## 3
## Holy See (Vatican City State)
## 3
## Honduras
## 5
## Hong Kong
## 6
## Hungary
## 6
## Iceland
## 3
## India
## 2
## Indonesia
## 6
## Iran
## 5
## Ireland
## 3
## Isle of Man
## 3
## Israel
## 4
## Italy
## 5
## Jamaica
## 5
## Japan
## 4
## Jersey
## 6
## Jordan
## 1
## Kazakhstan
## 4
## Kenya
## 4
## Kiribati
## 1
## Korea
## 5
## Kuwait
## 2
## Kyrgyz Republic
## 6
## Lao People's Democratic Republic
## 4
## Latvia
## 4
## Lebanon
## 6
## Lesotho
## 1
## Liberia
## 8
## Libyan Arab Jamahiriya
## 4
## Liechtenstein
## 6
## Lithuania
## 3
## Luxembourg
## 7
## Macao
## 3
## Macedonia
## 2
## Madagascar
## 6
## Malawi
## 4
## Malaysia
## 3
## Maldives
## 4
## Mali
## 4
## Malta
## 6
## Marshall Islands
## 1
## Martinique
## 4
## Mauritania
## 2
## Mauritius
## 4
## Mayotte
## 6
## Mexico
## 6
## Micronesia
## 8
## Moldova
## 6
## Monaco
## 3
## Mongolia
## 6
## Montenegro
## 2
## Montserrat
## 1
## Morocco
## 3
## Mozambique
## 1
## Myanmar
## 5
## Namibia
## 2
## Nauru
## 3
## Nepal
## 3
## Netherlands
## 4
## Netherlands Antilles
## 6
## New Caledonia
## 2
## New Zealand
## 4
## Nicaragua
## 3
## Niger
## 3
## Niue
## 3
## Norfolk Island
## 5
## Northern Mariana Islands
## 3
## Norway
## 2
## Pakistan
## 5
## Palau
## 4
## Palestinian Territory
## 3
## Panama
## 2
## Papua New Guinea
## 5
## Paraguay
## 3
## Peru
## 8
## Philippines
## 6
## Pitcairn Islands
## 2
## Poland
## 6
## Portugal
## 3
## Puerto Rico
## 6
## Qatar
## 6
## Reunion
## 2
## Romania
## 1
## Russian Federation
## 3
## Rwanda
## 5
## Saint Barthelemy
## 2
## Saint Helena
## 5
## Saint Kitts and Nevis
## 1
## Saint Lucia
## 2
## Saint Martin
## 4
## Saint Pierre and Miquelon
## 5
## Saint Vincent and the Grenadines
## 6
## Samoa
## 6
## San Marino
## 3
## Sao Tome and Principe
## 2
## Saudi Arabia
## 4
## Senegal
## 8
## Serbia
## 5
## Seychelles
## 3
## Sierra Leone
## 2
## Singapore
## 6
## Slovakia (Slovak Republic)
## 2
## Slovenia
## 1
## Somalia
## 5
## South Africa
## 8
## South Georgia and the South Sandwich Islands
## 2
## Spain
## 3
## Sri Lanka
## 4
## Sudan
## 2
## Suriname
## 2
## Svalbard & Jan Mayen Islands
## 6
## Swaziland
## 2
## Sweden
## 4
## Switzerland
## 4
## Syrian Arab Republic
## 3
## Taiwan
## 7
## Tajikistan
## 3
## Tanzania
## 3
## Thailand
## 4
## Timor-Leste
## 5
## Togo
## 3
## Tokelau
## 4
## Tonga
## 5
## Trinidad and Tobago
## 3
## Tunisia
## 4
## Turkey
## 8
## Turkmenistan
## 6
## Turks and Caicos Islands
## 5
## Tuvalu
## 4
## Uganda
## 4
## Ukraine
## 5
## United Arab Emirates
## 6
## United Kingdom
## 3
## United States Minor Outlying Islands
## 4
## United States of America
## 5
## United States Virgin Islands
## 4
## Uruguay
## 5
## Uzbekistan
## 2
## Vanuatu
## 6
## Venezuela
## 7
## Vietnam
## 3
## Wallis and Futuna
## 4
## Western Sahara
## 7
## Yemen
## 3
## Zambia
## 4
## Zimbabwe
## 6barplot(Country_frequency,xlab ="Country", col="yellow")
###5.1d “Country” variable frequencty barplot
City <- my_dataset$City
City_frequency<- table(City)
City_frequency## City
## Adamsbury Adamside Adamsstad
## 1 1 1
## Alanview Alexanderfurt Alexanderview
## 1 1 1
## Alexandrafort Alexisland Aliciatown
## 1 1 1
## Alvaradoport Alvarezland Amandafort
## 1 1 1
## Amandahaven Amandaland Amyfurt
## 1 1 1
## Amyhaven Andersonchester Andersonfurt
## 1 1 1
## Andersonton Andrewborough Andrewmouth
## 1 1 1
## Angelhaven Anthonyfurt Ashleychester
## 1 1 1
## Ashleymouth Austinborough Austinland
## 1 1 1
## Bakerhaven Barbershire Beckton
## 1 1 1
## Benjaminchester Bernardton Bethburgh
## 2 1 1
## Birdshire Blairborough Blairville
## 1 1 1
## Blevinstown Bowenview Boyerberg
## 1 1 1
## Bradleyborough Bradleyburgh Bradleyside
## 1 1 1
## Bradshawborough Bradyfurt Brandiland
## 1 1 1
## Brandonbury Brandonstad Brandymouth
## 1 1 1
## Brendaburgh Brendachester Brianabury
## 1 1 1
## Brianfurt Brianland Brittanyborough
## 1 1 1
## Brownbury Brownport Brownton
## 1 1 1
## Browntown Brownview Bruceburgh
## 1 1 1
## Burgessside Butlerfort Calebberg
## 1 1 1
## Cameronberg Campbellstad Cannonbury
## 1 1 1
## Carsonshire Carterburgh Carterland
## 1 1 1
## Carterport Carterton Cassandratown
## 1 1 1
## Catherinefort Cervantesshire Chapmanland
## 1 1 1
## Chapmanmouth Charlenetown Charlesbury
## 1 1 1
## Charlesport Charlottefort Chaseshire
## 1 1 1
## Chrismouth Christinehaven Christinetown
## 1 1 1
## Christopherchester Christopherport Christopherville
## 1 1 1
## Clarkborough Claytonside Clineshire
## 1 1 1
## Codyburgh Coffeytown Colebury
## 1 1 1
## Colemanshire Collinsburgh Combsstad
## 1 1 1
## Contrerasshire Costaburgh Courtneyfort
## 1 1 1
## Coxhaven Cranemouth Crawfordfurt
## 1 1 1
## Cunninghamhaven Curtisport Curtisview
## 1 1 1
## Cynthiaside Daisymouth Danielview
## 1 1 1
## Davidmouth Davidside Davidstad
## 1 1 1
## Davidton Davidview Daviesborough
## 1 1 1
## Davieshaven Davilachester Davisfurt
## 1 1 1
## Dayton Deannaville Debraburgh
## 1 1 1
## Derrickhaven Destinyfurt Dianashire
## 1 1 1
## Dianaville Donaldshire Douglasview
## 1 1 1
## Duffystad Dustinborough Dustinchester
## 1 1 1
## Dustinmouth East Aaron East Anthony
## 1 1 1
## East Barbara East Benjaminville East Breannafurt
## 1 1 1
## East Brettton East Brianberg East Brittanyville
## 1 1 1
## East Carlos East Christopher East Christopherbury
## 1 1 1
## East Connie East Dana East Deborahhaven
## 1 1 1
## East Debraborough East Donna East Donnatown
## 1 1 1
## East Eric East Ericport East Georgeside
## 1 1 1
## East Graceland East Heatherside East Heidi
## 1 1 1
## East Henry East Jason East Jennifer
## 1 1 1
## East Jessefort East John East Johnport
## 1 2 1
## East Kevinbury East Lindsey East Maureen
## 1 1 1
## East Michaelland East Michaelmouth East Michaeltown
## 1 1 1
## East Michele East Michelleberg East Mike
## 1 1 1
## East Paul East Rachaelfurt East Rachelview
## 1 1 1
## East Ronald East Samanthashire East Sharon
## 1 1 1
## East Shawn East Shawnchester East Sheriville
## 1 1 1
## East Stephen East Susanland East Tammie
## 1 1 1
## East Theresashire East Tiffanyport East Timothy
## 1 1 2
## East Timothyport East Toddfort East Troyhaven
## 1 1 1
## East Tylershire East Valerie East Vincentstad
## 1 1 1
## East Yvonnechester Edwardmouth Edwardsmouth
## 1 1 1
## Edwardsport Elizabethbury Elizabethmouth
## 1 1 1
## Elizabethport Elizabethstad Emilyfurt
## 1 1 1
## Ericksonmouth Erikville Erinmouth
## 1 1 1
## Erinton Estesfurt Estradafurt
## 1 1 1
## Estradashire Evansfurt Evansville
## 1 1 1
## Faithview Florestown Fosterside
## 1 1 1
## Frankbury Frankchester Frankport
## 1 1 1
## Fraziershire Garciamouth Garciaside
## 1 1 1
## Garciatown Garciaview Garnerberg
## 1 1 1
## Garrettborough Garychester Gilbertville
## 1 1 1
## Gomezport Gonzalezburgh Grahamberg
## 1 1 1
## Gravesport Greenechester Greentown
## 1 1 1
## Greerport Greerton Greghaven
## 1 1 1
## Guzmanland Haleberg Haleview
## 1 1 1
## Hallfort Hamiltonfort Hammondport
## 1 1 1
## Hannahside Hannaport Hansenland
## 1 1 1
## Hansenmouth Harmonhaven Harperborough
## 1 1 1
## Harrishaven Harrisonmouth Hartmanchester
## 1 1 1
## Hartport Harveyport Hatfieldshire
## 1 1 1
## Hawkinsbury Hayesmouth Heatherberg
## 1 1 1
## Helenborough Hendrixmouth Henryfort
## 1 1 1
## Henryland Hernandezchester Hernandezfort
## 1 1 1
## Hernandezside Hernandezville Hessstad
## 1 1 1
## Hintonport Hobbsbury Holderville
## 1 1 1
## Hollandberg Hollyfurt Hubbardmouth
## 1 1 1
## Huffmanchester Hughesport Hurleyborough
## 1 1 1
## Ianmouth Ingramberg Isaacborough
## 1 1 1
## Jacksonburgh Jacksonmouth Jacksonstad
## 1 1 1
## Jacobstad Jacquelineshire Jamesberg
## 1 1 1
## Jamesfurt Jamesmouth Jamesville
## 1 1 1
## Jamieberg Jamiefort Janiceview
## 1 1 1
## Jasminefort Jayville Jeffreyburgh
## 1 1 1
## Jeffreymouth Jeffreyshire Jenniferhaven
## 1 1 1
## Jenniferstad Jensenborough Jensenton
## 1 1 1
## Jeremybury Jeremyshire Jessicahaven
## 1 1 1
## Jessicashire Jessicastad Joanntown
## 1 1 1
## Joechester Johnport Johnsonfort
## 1 1 1
## Johnsontown Johnsonview Johnsport
## 1 1 1
## Johnstad Johnstonmouth Johnstonshire
## 2 1 1
## Jonathanland Jonathantown Jonesland
## 1 1 1
## Jonesmouth Jonesshire Joneston
## 1 1 2
## Jordanmouth Jordanshire Jordantown
## 1 1 1
## Josephberg Josephmouth Josephstad
## 1 1 1
## Joshuaburgh Joshuamouth Juanport
## 1 1 1
## Juliaport Julietown Karenmouth
## 1 1 1
## Karenton Katieport Kaylashire
## 1 1 1
## Keithtown Kellytown Kennedyfurt
## 1 1 1
## Kennethview Kentmouth Kevinberg
## 1 1 1
## Kevinchester Kimberlyhaven Kimberlymouth
## 1 1 1
## Kimberlytown Kingchester Kingshire
## 1 1 1
## Klineside Knappburgh Kristineberg
## 1 1 1
## Kristinfurt Kristintown Kyleborough
## 1 1 1
## Kylieview Lake Adrian Lake Allenville
## 1 1 1
## Lake Amanda Lake Amy Lake Angela
## 1 1 1
## Lake Annashire Lake Beckyburgh Lake Brandonview
## 1 1 1
## Lake Brian Lake Cassandraport Lake Charlottestad
## 1 1 1
## Lake Christopherfurt Lake Conniefurt Lake Courtney
## 1 1 1
## Lake Craigview Lake Cynthia Lake Danielle
## 1 1 1
## Lake David Lake Deannaborough Lake Deborahburgh
## 2 1 1
## Lake Dustin Lake Edward Lake Elizabethside
## 1 1 1
## Lake Evantown Lake Faith Lake Gerald
## 1 1 1
## Lake Hailey Lake Ian Lake Jacob
## 1 1 1
## Lake Jacqueline Lake James Lake Jasonchester
## 1 2 1
## Lake Jennifer Lake Jenniferton Lake Jessica
## 1 1 1
## Lake Jessicaville Lake Jesus Lake Jillville
## 1 1 1
## Lake John Lake Johnbury Lake Jonathanview
## 1 1 1
## Lake Jose Lake Joseph Lake Josetown
## 2 1 1
## Lake Joshuafurt Lake Kevin Lake Kurtmouth
## 1 1 1
## Lake Lisa Lake Matthew Lake Matthewland
## 1 1 1
## Lake Melindamouth Lake Michael Lake Michaelport
## 1 1 1
## Lake Michelle Lake Michellebury Lake Nicole
## 1 1 1
## Lake Patrick Lake Rhondaburgh Lake Stephenborough
## 2 1 1
## Lake Susan Lake Timothy Lake Tracy
## 2 1 1
## Lake Vanessa Lake Zacharyfurt Lauraburgh
## 1 1 1
## Laurieside Lawrenceborough Lawsonshire
## 1 1 1
## Leahside Leonchester Lesliebury
## 1 1 1
## Lesliefort Lewismouth Lindaside
## 1 1 1
## Lindsaymouth Lisaberg Lisafort
## 1 1 1
## Lisamouth Lopezberg Lopezmouth
## 3 1 1
## Loriville Lovemouth Luischester
## 1 1 1
## Luisfurt Lukeport Mackenziemouth
## 1 1 1
## Marcushaven Mariahview Mariebury
## 1 1 1
## Mariemouth Markhaven Masonhaven
## 1 1 1
## Masseyshire Mataberg Matthewtown
## 1 1 1
## Mauricefurt Mauriceshire Mcdonaldfort
## 1 1 1
## Mclaughlinbury Meaganfort Meghanchester
## 1 1 1
## Melanieton Melissachester Melissafurt
## 1 1 1
## Melissastad Meyerchester Meyersstad
## 1 1 1
## Mezaton Michaelland Michaelmouth
## 1 1 1
## Michaelshire Micheletown Michellefort
## 1 1 1
## Michelleside Millerbury Millerchester
## 2 2 1
## Millerfort Millerland Millerside
## 1 1 1
## Millertown Millerview Mollyport
## 2 1 1
## Monicaview Morganfort Morganport
## 1 1 1
## Morrismouth Mosleyburgh Mullenside
## 1 1 1
## Munozberg Murphymouth Nelsonfurt
## 1 1 1
## New Amanda New Angelview New Brandy
## 1 1 1
## New Brendafurt New Charleschester New Christinatown
## 1 1 1
## New Cynthia New Daniellefort New Darlene
## 1 1 1
## New Dawnland New Debbiestad New Denisebury
## 1 1 1
## New Frankshire New Gabriel New Henry
## 1 1 1
## New Hollyberg New James New Jamestown
## 1 1 1
## New Jasmine New Jay New Jeffreychester
## 1 1 1
## New Jessicaport New Johnberg New Joshuaport
## 2 1 1
## New Juan New Julianberg New Julie
## 1 1 1
## New Karenberg New Kayla New Keithburgh
## 1 1 1
## New Lindaberg New Lucasburgh New Marcusbury
## 1 1 1
## New Maria New Matthew New Michael
## 1 1 1
## New Michaeltown New Nancy New Nathan
## 1 1 1
## New Patriciashire New Patrick New Paul
## 1 1 1
## New Rachel New Rebecca New Sabrina
## 1 1 1
## New Sean New Shane New Sharon
## 1 1 1
## New Sheila New Sonialand New Steve
## 2 1 1
## New Tammy New Taylorburgh New Teresa
## 1 1 1
## New Theresa New Thomas New Timothy
## 1 1 1
## New Tina New Tinamouth New Traceystad
## 1 1 1
## New Travis New Travistown New Tyler
## 1 1 1
## New Wanda New Williammouth New Williamville
## 1 1 1
## Newmanberg Nicholasland Nicholasport
## 1 1 1
## North Aaronburgh North Aaronchester North Alexandra
## 1 1 1
## North Anaport North Andrew North Andrewstad
## 1 1 1
## North Angelastad North Angelatown North Anna
## 1 1 1
## North April North Brandon North Brittanyburgh
## 1 1 1
## North Cassie North Charlesbury North Christopher
## 1 1 1
## North Daniel North Debra North Debrashire
## 2 1 1
## North Derekville North Destiny North Elizabeth
## 1 1 1
## North Frankstad North Garyhaven North Isabellaville
## 1 1 1
## North Jenniferburgh North Jeremyport North Jessicaville
## 1 1 1
## North Johnside North Johntown North Jonathan
## 1 1 1
## North Joshua North Katie North Kennethside
## 1 1 1
## North Kevinside North Kimberly North Kristine
## 1 1 1
## North Lauraland North Laurenview North Leonmouth
## 1 1 1
## North Lisachester North Loriburgh North Mark
## 1 1 1
## North Maryland North Mercedes North Michael
## 1 1 1
## North Monicaville North Randy North Raymond
## 1 1 1
## North Regina North Ricardotown North Richardburgh
## 1 1 1
## North Ronaldshire North Russellborough North Samantha
## 1 1 1
## North Sarashire North Shannon North Stephanieberg
## 1 1 1
## North Tara North Tiffany North Tracyport
## 1 1 1
## North Tylerland North Virginia North Wesleychester
## 1 1 1
## Novaktown Odomville Olsonside
## 1 1 1
## Olsonstad Palmerside Pamelamouth
## 1 1 2
## Parkerhaven Patriciahaven Patrickmouth
## 1 1 1
## Pattymouth Paulhaven Paulport
## 1 1 1
## Paulshire Pearsonfort Penatown
## 1 1 1
## Perezland Perryburgh Petersonfurt
## 1 1 1
## Phelpschester Philipberg Phillipsbury
## 1 1 1
## Port Aliciabury Port Angelamouth Port Anthony
## 1 1 1
## Port Aprilville Port Beth Port Blake
## 1 1 1
## Port Brenda Port Brian Port Brianfort
## 1 1 1
## Port Brittanyville Port Brookeland Port Calvintown
## 1 1 1
## Port Cassie Port Chasemouth Port Christina
## 1 1 1
## Port Christinemouth Port Christopher Port Christopherborough
## 1 1 1
## Port Crystal Port Daniel Port Danielleberg
## 1 1 1
## Port Davidland Port Dennis Port Derekberg
## 1 1 1
## Port Destiny Port Douglasborough Port Elijah
## 1 1 1
## Port Eric Port Erikhaven Port Erinberg
## 1 1 1
## Port Eugeneport Port Georgebury Port Gregory
## 1 1 1
## Port Jacqueline Port Jacquelinestad Port James
## 1 1 1
## Port Jasmine Port Jason Port Jefferybury
## 1 2 1
## Port Jeffrey Port Jennifer Port Jessica
## 1 1 1
## Port Jessicamouth Port Jodi Port Joshuafort
## 1 1 1
## Port Juan Port Julie Port Karenfurt
## 2 2 1
## Port Katelynview Port Kathleenfort Port Kevinborough
## 1 1 1
## Port Lawrence Port Maria Port Mathew
## 1 1 1
## Port Melissaberg Port Melissastad Port Michaelmouth
## 1 1 1
## Port Michealburgh Port Mitchell Port Patrickton
## 1 1 1
## Port Paultown Port Rachel Port Raymondfort
## 1 1 1
## Port Robin Port Sarahhaven Port Sarahshire
## 1 1 1
## Port Sherrystad Port Stacey Port Stacy
## 1 1 1
## Port Susan Port Whitneyhaven Portermouth
## 1 1 1
## Pottermouth Princebury Pruittmouth
## 1 1 1
## Rachelhaven Ramirezhaven Ramirezland
## 1 1 1
## Ramirezside Ramirezton Ramosstad
## 1 1 1
## Randolphport Randyshire Rebeccamouth
## 1 1 1
## Reginamouth Reneechester Reyesfurt
## 1 1 1
## Reyesland Rhondaborough Richardshire
## 1 1 1
## Richardsland Richardsonland Richardsonmouth
## 1 1 1
## Richardsonshire Richardsontown Rickymouth
## 1 1 1
## Riggsstad Rivasland Robertbury
## 1 1 1
## Robertfurt Robertmouth Robertside
## 2 1 1
## Robertsonburgh Robertstown Roberttown
## 1 1 1
## Robinsonland Robinsontown Rochabury
## 1 1 1
## Rogerburgh Rogerland Ronaldport
## 1 1 1
## Ronniemouth Russellville Ryanhaven
## 1 1 1
## Sabrinaview Salazarbury Samanthaland
## 1 1 1
## Samuelborough Sanchezland Sanchezmouth
## 1 1 1
## Sandersland Sanderstown Sandraland
## 1 1 1
## Sandrashire Sandraville Sarafurt
## 1 1 1
## Sarahland Sarahton Sellerstown
## 1 1 1
## Shaneland Sharpberg Shawnside
## 1 1 1
## Shawstad Shelbyport Sherrishire
## 1 2 1
## Shirleyfort Silvaton Smithburgh
## 1 1 1
## Smithside Smithtown South Aaron
## 1 1 1
## South Adam South Adamhaven South Alexisborough
## 1 1 1
## South Blakestad South Brian South Cathyfurt
## 1 1 1
## South Christopher South Corey South Cynthiashire
## 1 1 1
## South Daniel South Daniellefort South Davidhaven
## 1 1 1
## South Davidmouth South Denise South Denisefurt
## 1 1 1
## South Dianeshire South George South Henry
## 1 1 1
## South Jackieberg South Jade South Jaimeview
## 1 1 1
## South Jasminebury South Jeanneport South Jennifer
## 1 1 1
## South Jessica South John South Johnnymouth
## 1 1 1
## South Kyle South Lauraton South Lauratown
## 1 1 1
## South Lisa South Manuel South Margaret
## 2 1 1
## South Mark South Meghan South Meredithmouth
## 1 1 1
## South Pamela South Patrickfort South Peter
## 1 1 1
## South Rebecca South Renee South Robert
## 1 1 1
## South Ronald South Stephanieport South Tiffanyton
## 1 1 1
## South Tomside South Troy South Vincentchester
## 1 1 1
## South Walter Staceyfort Stephenborough
## 1 1 1
## Stewartbury Suzannetown Sylviaview
## 1 1 1
## Tammymouth Tammyshire Taylorberg
## 1 1 1
## Taylorhaven Taylormouth Taylorport
## 1 1 1
## Teresahaven Thomasstad Thomasview
## 1 1 1
## Timothyfurt Timothymouth Timothyport
## 1 1 1
## Timothytown Tinachester Tinaton
## 1 1 1
## Townsendfurt Tracyhaven Tranland
## 1 1 1
## Troyville Turnerchester Turnerview
## 1 1 1
## Turnerville Tylerport Valerieland
## 1 1 1
## Vanessastad Vanessaview Villanuevastad
## 1 1 1
## Villanuevaton Wademouth Wadestad
## 1 1 1
## Wagnerchester Wallacechester Walshhaven
## 1 1 1
## Waltertown Watsonfort Welchshire
## 1 1 1
## Wendyton Wendyville West Alice
## 1 1 1
## West Alyssa West Amanda West Andrew
## 1 2 1
## West Angela West Angelabury West Annefort
## 1 1 1
## West Aprilport West Arielstad West Barbara
## 1 1 1
## West Benjamin West Brad West Brandonton
## 1 1 1
## West Brenda West Carmenfurt West Casey
## 1 1 1
## West Chloeborough West Christopher West Colin
## 1 1 1
## West Connor West Courtney West Daleborough
## 1 1 1
## West Dannyberg West David West Dennis
## 1 1 1
## West Derekmouth West Dylanberg West Eduardotown
## 1 1 1
## West Ericaport West Ericfurt West Gabriellamouth
## 1 1 1
## West Gregburgh West Guybury West James
## 1 1 1
## West Jane West Jeremyside West Jessicahaven
## 1 1 1
## West Jodi West Joseph West Julia
## 1 1 1
## West Justin West Katiefurt West Kevinfurt
## 1 1 1
## West Lacey West Leahton West Lindseybury
## 1 1 1
## West Lisa West Lucas West Mariafort
## 1 1 1
## West Melaniefurt West Melissashire West Michaelhaven
## 1 1 1
## West Michaelport West Michaelshire West Michaelstad
## 1 1 1
## West Pamela West Randy West Raymondmouth
## 1 1 1
## West Rhondamouth West Ricardo West Richard
## 1 1 1
## West Robertside West Roytown West Russell
## 1 1 1
## West Ryan West Samantha West Shannon
## 1 1 2
## West Sharon West Shaun West Steven
## 1 1 2
## West Sydney West Tanner West Tanya
## 1 1 1
## West Terrifurt West Thomas West Tinashire
## 1 1 1
## West Travismouth West Wendyland West William
## 1 1 1
## West Zacharyborough Westshire Whiteport
## 1 1 1
## Whitneyfort Wilcoxport Williammouth
## 1 1 1
## Williamport Williamsborough Williamsfort
## 1 1 1
## Williamsmouth Williamsport Williamsside
## 1 3 1
## Williamstad Wilsonburgh Wintersfort
## 1 1 1
## Wongland Wrightburgh Wrightview
## 1 2 1
## Yangside Youngburgh Youngfort
## 1 1 1
## Yuton Zacharystad Zacharyton
## 1 1 1barplot(City_frequency,xlab ="City", col="grey")
###5.1e “Topic.Line” variable frequencty barplot
Topic <- my_dataset$Ad.Topic.Line
Topic_frequency<- table(Topic)
Topic_frequency## Topic
## Adaptive 24hour Graphic Interface
## 1
## Adaptive asynchronous attitude
## 1
## Adaptive context-sensitive application
## 1
## Adaptive contextually-based methodology
## 1
## Adaptive demand-driven knowledgebase
## 1
## Adaptive uniform capability
## 1
## Advanced 24/7 productivity
## 1
## Advanced 5thgeneration capability
## 1
## Advanced didactic conglomeration
## 1
## Advanced disintermediate data-warehouse
## 1
## Advanced exuding conglomeration
## 1
## Advanced full-range migration
## 1
## Advanced heuristic firmware
## 1
## Advanced local task-force
## 1
## Advanced modular Local Area Network
## 1
## Advanced systemic productivity
## 1
## Advanced web-enabled standardization
## 1
## Ameliorated actuating workforce
## 1
## Ameliorated bandwidth-monitored contingency
## 1
## Ameliorated client-driven forecast
## 1
## Ameliorated coherent open architecture
## 1
## Ameliorated contextually-based collaboration
## 1
## Ameliorated discrete extranet
## 1
## Ameliorated exuding encryption
## 1
## Ameliorated exuding solution
## 1
## Ameliorated intermediate Graphical User Interface
## 1
## Ameliorated leadingedge help-desk
## 1
## Ameliorated local workforce
## 1
## Ameliorated tangible hierarchy
## 1
## Ameliorated upward-trending definition
## 1
## Ameliorated user-facing help-desk
## 1
## Ameliorated well-modulated complexity
## 1
## Assimilated actuating policy
## 1
## Assimilated discrete strategy
## 1
## Assimilated encompassing portal
## 1
## Assimilated fault-tolerant hub
## 1
## Assimilated homogeneous service-desk
## 1
## Assimilated hybrid initiative
## 1
## Assimilated multi-state paradigm
## 1
## Assimilated next generation firmware
## 1
## Assimilated stable encryption
## 1
## Automated client-driven orchestration
## 1
## Automated coherent flexibility
## 1
## Automated directional function
## 1
## Automated full-range Internet solution
## 1
## Automated mobile model
## 1
## Automated multi-state toolset
## 1
## Automated object-oriented firmware
## 1
## Automated stable help-desk
## 1
## Automated static concept
## 1
## Automated web-enabled migration
## 1
## Balanced 4thgeneration success
## 1
## Balanced actuating moderator
## 1
## Balanced asynchronous hierarchy
## 1
## Balanced contextually-based pricing structure
## 1
## Balanced discrete approach
## 1
## Balanced disintermediate conglomeration
## 1
## Balanced dynamic application
## 1
## Balanced empowering success
## 1
## Balanced executive definition
## 1
## Balanced heuristic approach
## 1
## Balanced mobile Local Area Network
## 1
## Balanced motivating help-desk
## 1
## Balanced responsive open system
## 1
## Balanced uniform algorithm
## 1
## Balanced value-added database
## 1
## Business-focused asynchronous budgetary management
## 1
## Business-focused background synergy
## 1
## Business-focused client-driven forecast
## 1
## Business-focused encompassing neural-net
## 1
## Business-focused high-level hardware
## 1
## Business-focused holistic benchmark
## 1
## Business-focused maximized complexity
## 1
## Business-focused real-time toolset
## 1
## Business-focused responsive website
## 1
## Business-focused transitional solution
## 1
## Business-focused user-facing benchmark
## 1
## Business-focused value-added definition
## 1
## Centralized 24/7 installation
## 1
## Centralized 24hour synergy
## 1
## Centralized asynchronous portal
## 1
## Centralized clear-thinking Graphic Interface
## 1
## Centralized client-driven workforce
## 1
## Centralized content-based focus group
## 1
## Centralized logistical secured line
## 1
## Centralized multi-state hierarchy
## 1
## Centralized neutral neural-net
## 1
## Centralized systematic knowledgebase
## 1
## Centralized tertiary pricing structure
## 1
## Centralized user-facing service-desk
## 1
## Centralized value-added hierarchy
## 1
## Cloned 5thgeneration orchestration
## 1
## Cloned analyzing artificial intelligence
## 1
## Cloned dedicated analyzer
## 1
## Cloned explicit middleware
## 1
## Cloned incremental matrices
## 1
## Cloned object-oriented benchmark
## 1
## Cloned optimal leverage
## 1
## Compatible composite project
## 1
## Compatible dedicated productivity
## 1
## Compatible intangible customer loyalty
## 1
## Compatible intermediate concept
## 1
## Compatible scalable emulation
## 1
## Compatible systemic function
## 1
## Configurable 24/7 hub
## 1
## Configurable asynchronous application
## 1
## Configurable bottom-line application
## 1
## Configurable coherent function
## 1
## Configurable disintermediate throughput
## 1
## Configurable dynamic adapter
## 1
## Configurable dynamic secured line
## 1
## Configurable fault-tolerant monitoring
## 1
## Configurable impactful capacity
## 1
## Configurable impactful firmware
## 1
## Configurable impactful productivity
## 1
## Configurable interactive contingency
## 1
## Configurable logistical Graphical User Interface
## 1
## Configurable mission-critical algorithm
## 1
## Configurable multi-state utilization
## 1
## Configurable tertiary budgetary management
## 1
## Configurable tertiary capability
## 1
## Cross-group global orchestration
## 1
## Cross-group human-resource time-frame
## 1
## Cross-group neutral synergy
## 1
## Cross-group non-volatile secured line
## 1
## Cross-group regional website
## 1
## Cross-group systemic customer loyalty
## 1
## Cross-group value-added success
## 1
## Cross-platform 4thgeneration focus group
## 1
## Cross-platform client-server hierarchy
## 1
## Cross-platform directional intranet
## 1
## Cross-platform logistical pricing structure
## 1
## Cross-platform multimedia algorithm
## 1
## Cross-platform neutral system engine
## 1
## Cross-platform regional task-force
## 1
## Cross-platform zero-defect structure
## 1
## Customer-focused 24/7 concept
## 1
## Customer-focused attitude-oriented instruction set
## 1
## Customer-focused empowering ability
## 1
## Customer-focused explicit challenge
## 1
## Customer-focused fault-tolerant implementation
## 1
## Customer-focused full-range neural-net
## 1
## Customer-focused impactful success
## 1
## Customer-focused incremental system engine
## 1
## Customer-focused multi-tasking Internet solution
## 1
## Customer-focused optimizing moderator
## 1
## Customer-focused solution-oriented software
## 1
## Customer-focused system-worthy superstructure
## 1
## Customer-focused transitional strategy
## 1
## Customer-focused upward-trending contingency
## 1
## Customer-focused zero-defect process improvement
## 1
## Customizable 6thgeneration knowledge user
## 1
## Customizable executive software
## 1
## Customizable holistic archive
## 1
## Customizable homogeneous contingency
## 1
## Customizable hybrid system engine
## 1
## Customizable methodical Graphical User Interface
## 1
## Customizable mission-critical adapter
## 1
## Customizable modular Internet solution
## 1
## Customizable multi-tasking website
## 1
## Customizable systematic service-desk
## 1
## Customizable tangible hierarchy
## 1
## Customizable value-added project
## 1
## Customizable zero-defect Internet solution
## 1
## Customizable zero-defect matrix
## 1
## De-engineered actuating hierarchy
## 1
## De-engineered attitude-oriented projection
## 1
## De-engineered fault-tolerant database
## 1
## De-engineered intangible flexibility
## 1
## De-engineered mobile infrastructure
## 1
## De-engineered object-oriented protocol
## 1
## De-engineered solution-oriented open architecture
## 1
## De-engineered tertiary secured line
## 1
## Decentralized 24hour approach
## 1
## Decentralized attitude-oriented interface
## 1
## Decentralized bottom-line help-desk
## 1
## Decentralized client-driven data-warehouse
## 1
## Decentralized foreground infrastructure
## 1
## Decentralized methodical capability
## 1
## Decentralized needs-based analyzer
## 1
## Decentralized real-time circuit
## 1
## Devolved exuding Local Area Network
## 1
## Devolved human-resource circuit
## 1
## Devolved regional moderator
## 1
## Devolved responsive structure
## 1
## Devolved tangible approach
## 1
## Devolved zero administration intranet
## 1
## Digitized content-based circuit
## 1
## Digitized contextually-based product
## 1
## Digitized disintermediate ability
## 1
## Digitized global capability
## 1
## Digitized heuristic solution
## 1
## Digitized homogeneous core
## 1
## Digitized interactive initiative
## 1
## Digitized radical architecture
## 1
## Digitized radical array
## 1
## Digitized static capability
## 1
## Digitized zero-defect implementation
## 1
## Digitized zero administration paradigm
## 1
## Distributed 3rdgeneration definition
## 1
## Distributed bifurcated challenge
## 1
## Distributed cohesive migration
## 1
## Distributed fault-tolerant service-desk
## 1
## Distributed intangible database
## 1
## Distributed leadingedge orchestration
## 1
## Distributed maximized ability
## 1
## Distributed scalable orchestration
## 1
## Distributed tertiary system engine
## 1
## Diverse background ability
## 1
## Diverse directional hardware
## 1
## Diverse executive groupware
## 1
## Diverse leadingedge website
## 1
## Diverse modular interface
## 1
## Diverse multi-tasking parallelism
## 1
## Diverse stable circuit
## 1
## Down-sized background groupware
## 1
## Down-sized bandwidth-monitored core
## 1
## Down-sized explicit budgetary management
## 1
## Down-sized modular intranet
## 1
## Down-sized uniform info-mediaries
## 1
## Down-sized well-modulated archive
## 1
## Enhanced asymmetric installation
## 1
## Enhanced dedicated support
## 1
## Enhanced homogeneous moderator
## 1
## Enhanced intangible portal
## 1
## Enhanced intermediate standardization
## 1
## Enhanced maximized access
## 1
## Enhanced methodical database
## 1
## Enhanced optimizing website
## 1
## Enhanced regional conglomeration
## 1
## Enhanced system-worthy application
## 1
## Enhanced system-worthy toolset
## 1
## Enhanced systematic adapter
## 1
## Enhanced systemic benchmark
## 1
## Enhanced tertiary utilization
## 1
## Enhanced zero tolerance Graphic Interface
## 1
## Enterprise-wide bi-directional secured line
## 1
## Enterprise-wide client-driven contingency
## 1
## Enterprise-wide foreground emulation
## 1
## Enterprise-wide incremental Internet solution
## 1
## Enterprise-wide local matrices
## 1
## Enterprise-wide tangible model
## 1
## Ergonomic 24/7 solution
## 1
## Ergonomic client-driven application
## 1
## Ergonomic empowering frame
## 1
## Ergonomic full-range time-frame
## 1
## Ergonomic methodical encoding
## 1
## Ergonomic multi-state structure
## 1
## Ergonomic neutral portal
## 1
## Ergonomic zero tolerance encoding
## 1
## Exclusive client-driven model
## 1
## Exclusive cohesive intranet
## 1
## Exclusive discrete firmware
## 1
## Exclusive disintermediate Internet solution
## 1
## Exclusive disintermediate task-force
## 1
## Exclusive even-keeled moratorium
## 1
## Exclusive multi-state Internet solution
## 1
## Exclusive neutral parallelism
## 1
## Exclusive systematic algorithm
## 1
## Exclusive zero tolerance alliance
## 1
## Exclusive zero tolerance frame
## 1
## Expanded clear-thinking core
## 1
## Expanded full-range synergy
## 1
## Expanded intangible solution
## 1
## Expanded modular application
## 1
## Expanded radical software
## 1
## Expanded value-added emulation
## 1
## Expanded zero administration attitude
## 1
## Extended analyzing emulation
## 1
## Extended context-sensitive monitoring
## 1
## Extended grid-enabled hierarchy
## 1
## Extended interactive model
## 1
## Extended leadingedge solution
## 1
## Extended local methodology
## 1
## Extended systemic policy
## 1
## Face-to-face analyzing encryption
## 1
## Face-to-face dedicated flexibility
## 1
## Face-to-face even-keeled website
## 1
## Face-to-face executive encryption
## 1
## Face-to-face intermediate approach
## 1
## Face-to-face methodical intranet
## 1
## Face-to-face mission-critical definition
## 1
## Face-to-face modular budgetary management
## 1
## Face-to-face multimedia success
## 1
## Face-to-face reciprocal methodology
## 1
## Face-to-face responsive alliance
## 1
## Focused 24hour implementation
## 1
## Focused 3rdgeneration pricing structure
## 1
## Focused coherent success
## 1
## Focused fresh-thinking Graphic Interface
## 1
## Focused high-level conglomeration
## 1
## Focused high-level frame
## 1
## Focused incremental Graphic Interface
## 1
## Focused intangible moderator
## 1
## Focused multi-state workforce
## 1
## Focused multimedia implementation
## 1
## Focused scalable complexity
## 1
## Focused systemic benchmark
## 1
## Focused upward-trending core
## 1
## Focused web-enabled Graphical User Interface
## 1
## Front-line actuating functionalities
## 1
## Front-line bandwidth-monitored capacity
## 1
## Front-line bifurcated ability
## 1
## Front-line dynamic model
## 1
## Front-line even-keeled website
## 1
## Front-line fault-tolerant intranet
## 1
## Front-line fresh-thinking installation
## 1
## Front-line fresh-thinking open system
## 1
## Front-line heuristic data-warehouse
## 1
## Front-line incremental access
## 1
## Front-line intermediate database
## 1
## Front-line methodical utilization
## 1
## Front-line multi-state hub
## 1
## Front-line neutral alliance
## 1
## Front-line non-volatile implementation
## 1
## Front-line system-worthy flexibility
## 1
## Front-line systemic capability
## 1
## Front-line tangible alliance
## 1
## Front-line upward-trending groupware
## 1
## Front-line zero-defect array
## 1
## Fully-configurable 5thgeneration circuit
## 1
## Fully-configurable asynchronous firmware
## 1
## Fully-configurable clear-thinking throughput
## 1
## Fully-configurable client-driven customer loyalty
## 1
## Fully-configurable context-sensitive Graphic Interface
## 1
## Fully-configurable eco-centric frame
## 1
## Fully-configurable foreground solution
## 1
## Fully-configurable high-level groupware
## 1
## Fully-configurable high-level implementation
## 1
## Fully-configurable holistic throughput
## 1
## Fully-configurable incremental Graphical User Interface
## 1
## Fully-configurable neutral open system
## 1
## Fully-configurable systemic productivity
## 1
## Function-based context-sensitive secured line
## 1
## Function-based directional productivity
## 1
## Function-based executive moderator
## 1
## Function-based fault-tolerant model
## 1
## Function-based incremental standardization
## 1
## Function-based optimizing extranet
## 1
## Function-based optimizing protocol
## 1
## Function-based stable alliance
## 1
## Function-based transitional complexity
## 1
## Fundamental clear-thinking knowledgebase
## 1
## Fundamental fault-tolerant neural-net
## 1
## Fundamental methodical support
## 1
## Fundamental modular algorithm
## 1
## Fundamental tangible moratorium
## 1
## Fundamental zero tolerance solution
## 1
## Future-proofed coherent budgetary management
## 1
## Future-proofed coherent hardware
## 1
## Future-proofed fresh-thinking conglomeration
## 1
## Future-proofed grid-enabled implementation
## 1
## Future-proofed holistic superstructure
## 1
## Future-proofed methodical protocol
## 1
## Future-proofed modular utilization
## 1
## Future-proofed responsive matrix
## 1
## Future-proofed stable function
## 1
## Grass-roots 4thgeneration forecast
## 1
## Grass-roots coherent extranet
## 1
## Grass-roots cohesive monitoring
## 1
## Grass-roots eco-centric instruction set
## 1
## Grass-roots empowering paradigm
## 1
## Grass-roots impactful system engine
## 1
## Grass-roots mission-critical emulation
## 1
## Grass-roots multimedia policy
## 1
## Grass-roots solution-oriented conglomeration
## 1
## Grass-roots systematic hardware
## 1
## Grass-roots transitional flexibility
## 1
## Horizontal client-driven hierarchy
## 1
## Horizontal client-server database
## 1
## Horizontal content-based synergy
## 1
## Horizontal even-keeled challenge
## 1
## Horizontal global leverage
## 1
## Horizontal heuristic support
## 1
## Horizontal heuristic synergy
## 1
## Horizontal high-level concept
## 1
## Horizontal hybrid challenge
## 1
## Horizontal incremental website
## 1
## Horizontal intermediate monitoring
## 1
## Horizontal modular success
## 1
## Horizontal multi-state interface
## 1
## Horizontal national architecture
## 1
## Horizontal transitional challenge
## 1
## Implemented asynchronous application
## 1
## Implemented bifurcated workforce
## 1
## Implemented bottom-line implementation
## 1
## Implemented context-sensitive Local Area Network
## 1
## Implemented didactic support
## 1
## Implemented discrete frame
## 1
## Implemented disintermediate attitude
## 1
## Implemented uniform synergy
## 1
## Innovative background conglomeration
## 1
## Innovative cohesive pricing structure
## 1
## Innovative executive encoding
## 1
## Innovative homogeneous alliance
## 1
## Innovative interactive portal
## 1
## Innovative maximized groupware
## 1
## Innovative regional groupware
## 1
## Innovative regional structure
## 1
## Innovative user-facing extranet
## 1
## Integrated 3rdgeneration monitoring
## 1
## Integrated client-server definition
## 1
## Integrated coherent pricing structure
## 1
## Integrated encompassing support
## 1
## Integrated grid-enabled budgetary management
## 1
## Integrated human-resource encoding
## 1
## Integrated impactful groupware
## 1
## Integrated interactive support
## 1
## Integrated leadingedge frame
## 1
## Integrated maximized service-desk
## 1
## Integrated motivating neural-net
## 1
## Intuitive dynamic attitude
## 1
## Intuitive explicit conglomeration
## 1
## Intuitive explicit firmware
## 1
## Intuitive exuding service-desk
## 1
## Intuitive fresh-thinking moderator
## 1
## Intuitive global website
## 1
## Intuitive modular system engine
## 1
## Intuitive radical forecast
## 1
## Intuitive transitional artificial intelligence
## 1
## Intuitive zero-defect framework
## 1
## Intuitive zero administration adapter
## 1
## Inverse asymmetric instruction set
## 1
## Inverse bi-directional knowledge user
## 1
## Inverse discrete extranet
## 1
## Inverse high-level capability
## 1
## Inverse local hub
## 1
## Inverse national core
## 1
## Inverse next generation moratorium
## 1
## Inverse stable synergy
## 1
## Inverse zero-defect capability
## 1
## Inverse zero tolerance customer loyalty
## 1
## Managed 24hour analyzer
## 1
## Managed 5thgeneration time-frame
## 1
## Managed 6thgeneration hierarchy
## 1
## Managed attitude-oriented Internet solution
## 1
## Managed client-server access
## 1
## Managed didactic flexibility
## 1
## Managed disintermediate capability
## 1
## Managed disintermediate matrices
## 1
## Managed eco-centric encoding
## 1
## Managed grid-enabled standardization
## 1
## Managed impactful definition
## 1
## Managed national hardware
## 1
## Managed upward-trending instruction set
## 1
## Managed well-modulated collaboration
## 1
## Managed zero tolerance concept
## 1
## Mandatory 3rdgeneration moderator
## 1
## Mandatory 4thgeneration structure
## 1
## Mandatory coherent groupware
## 1
## Mandatory dedicated data-warehouse
## 1
## Mandatory disintermediate info-mediaries
## 1
## Mandatory disintermediate utilization
## 1
## Mandatory empowering focus group
## 1
## Mandatory homogeneous architecture
## 1
## Monitored 24/7 moratorium
## 1
## Monitored content-based implementation
## 1
## Monitored context-sensitive initiative
## 1
## Monitored dynamic instruction set
## 1
## Monitored executive architecture
## 1
## Monitored explicit hierarchy
## 1
## Monitored homogeneous artificial intelligence
## 1
## Monitored intermediate circuit
## 1
## Monitored local Internet solution
## 1
## Monitored national standardization
## 1
## Monitored object-oriented Graphic Interface
## 1
## Monitored real-time superstructure
## 1
## Monitored systematic hierarchy
## 1
## Monitored zero administration collaboration
## 1
## Multi-channeled 3rdgeneration model
## 1
## Multi-channeled asymmetric installation
## 1
## Multi-channeled asynchronous open system
## 1
## Multi-channeled attitude-oriented toolset
## 1
## Multi-channeled mission-critical success
## 1
## Multi-channeled non-volatile website
## 1
## Multi-channeled reciprocal artificial intelligence
## 1
## Multi-channeled scalable moratorium
## 1
## Multi-lateral 24/7 Internet solution
## 1
## Multi-lateral attitude-oriented adapter
## 1
## Multi-lateral empowering throughput
## 1
## Multi-lateral motivating circuit
## 1
## Multi-lateral multi-state encryption
## 1
## Multi-layered 4thgeneration knowledge user
## 1
## Multi-layered fresh-thinking neural-net
## 1
## Multi-layered fresh-thinking process improvement
## 1
## Multi-layered non-volatile Graphical User Interface
## 1
## Multi-layered secondary software
## 1
## Multi-layered stable encoding
## 1
## Multi-layered tangible portal
## 1
## Multi-layered user-facing paradigm
## 1
## Multi-layered user-facing parallelism
## 1
## Multi-tiered foreground Graphic Interface
## 1
## Multi-tiered heuristic strategy
## 1
## Multi-tiered human-resource structure
## 1
## Multi-tiered interactive neural-net
## 1
## Multi-tiered maximized archive
## 1
## Multi-tiered mobile encoding
## 1
## Multi-tiered multi-state moderator
## 1
## Multi-tiered real-time implementation
## 1
## Multi-tiered stable leverage
## 1
## Networked asymmetric infrastructure
## 1
## Networked client-server solution
## 1
## Networked coherent interface
## 1
## Networked even-keeled workforce
## 1
## Networked foreground definition
## 1
## Networked high-level structure
## 1
## Networked impactful framework
## 1
## Networked local secured line
## 1
## Networked logistical info-mediaries
## 1
## Networked non-volatile synergy
## 1
## Networked regional Local Area Network
## 1
## Networked responsive application
## 1
## Networked stable array
## 1
## Networked stable open architecture
## 1
## Object-based executive productivity
## 1
## Object-based leadingedge complexity
## 1
## Object-based modular functionalities
## 1
## Object-based motivating instruction set
## 1
## Object-based neutral policy
## 1
## Object-based optimal solution
## 1
## Object-based reciprocal knowledgebase
## 1
## Object-based system-worthy superstructure
## 1
## Open-architected full-range projection
## 1
## Open-architected impactful productivity
## 1
## Open-architected intangible strategy
## 1
## Open-architected needs-based customer loyalty
## 1
## Open-architected system-worthy ability
## 1
## Open-architected system-worthy task-force
## 1
## Open-architected web-enabled benchmark
## 1
## Open-architected zero administration secured line
## 1
## Open-source 5thgeneration leverage
## 1
## Open-source coherent monitoring
## 1
## Open-source coherent policy
## 1
## Open-source even-keeled database
## 1
## Open-source global strategy
## 1
## Open-source holistic productivity
## 1
## Open-source local approach
## 1
## Open-source optimizing parallelism
## 1
## Open-source scalable protocol
## 1
## Open-source stable paradigm
## 1
## Operative actuating installation
## 1
## Operative didactic Local Area Network
## 1
## Operative full-range forecast
## 1
## Operative multi-tasking Graphic Interface
## 1
## Operative scalable emulation
## 1
## Operative secondary functionalities
## 1
## Operative stable moderator
## 1
## Operative system-worthy protocol
## 1
## Optimized 5thgeneration moratorium
## 1
## Optimized attitude-oriented initiative
## 1
## Optimized coherent Internet solution
## 1
## Optimized intermediate help-desk
## 1
## Optimized multimedia website
## 1
## Optimized static archive
## 1
## Optimized systemic capability
## 1
## Optimized upward-trending productivity
## 1
## Optional contextually-based flexibility
## 1
## Optional full-range projection
## 1
## Optional mission-critical functionalities
## 1
## Optional modular throughput
## 1
## Optional multi-state hardware
## 1
## Optional regional throughput
## 1
## Optional secondary access
## 1
## Optional tangible productivity
## 1
## Organic 3rdgeneration encryption
## 1
## Organic asynchronous hierarchy
## 1
## Organic bottom-line service-desk
## 1
## Organic contextually-based focus group
## 1
## Organic interactive support
## 1
## Organic leadingedge secured line
## 1
## Organic logistical adapter
## 1
## Organic motivating model
## 1
## Organic next generation matrix
## 1
## Organic well-modulated database
## 1
## Organized 24/7 middleware
## 1
## Organized client-driven alliance
## 1
## Organized contextually-based customer loyalty
## 1
## Organized demand-driven knowledgebase
## 1
## Organized empowering policy
## 1
## Organized global flexibility
## 1
## Organized global model
## 1
## Organized static focus group
## 1
## Organized upward-trending contingency
## 1
## Persevering 5thgeneration knowledge user
## 1
## Persevering eco-centric flexibility
## 1
## Persevering even-keeled help-desk
## 1
## Persevering exuding system engine
## 1
## Persevering needs-based open architecture
## 1
## Persevering reciprocal firmware
## 1
## Persevering tertiary capability
## 1
## Persistent demand-driven interface
## 1
## Persistent even-keeled application
## 1
## Persistent fault-tolerant service-desk
## 1
## Persistent homogeneous framework
## 1
## Phased 5thgeneration open system
## 1
## Phased analyzing emulation
## 1
## Phased clear-thinking encoding
## 1
## Phased content-based middleware
## 1
## Phased dynamic customer loyalty
## 1
## Phased fault-tolerant definition
## 1
## Phased full-range hardware
## 1
## Phased hybrid intranet
## 1
## Phased hybrid superstructure
## 1
## Phased leadingedge budgetary management
## 1
## Phased transitional instruction set
## 1
## Phased zero-defect portal
## 1
## Phased zero administration success
## 1
## Phased zero tolerance extranet
## 1
## Polarized 5thgeneration matrix
## 1
## Polarized 6thgeneration info-mediaries
## 1
## Polarized analyzing concept
## 1
## Polarized analyzing intranet
## 1
## Polarized attitude-oriented superstructure
## 1
## Polarized bandwidth-monitored moratorium
## 1
## Polarized bifurcated array
## 1
## Polarized clear-thinking budgetary management
## 1
## Polarized dynamic throughput
## 1
## Polarized intangible encoding
## 1
## Polarized logistical hub
## 1
## Polarized mission-critical structure
## 1
## Polarized modular function
## 1
## Polarized multimedia system engine
## 1
## Polarized tangible collaboration
## 1
## Pre-emptive client-driven secured line
## 1
## Pre-emptive client-server installation
## 1
## Pre-emptive client-server open system
## 1
## Pre-emptive cohesive budgetary management
## 1
## Pre-emptive content-based focus group
## 1
## Pre-emptive content-based frame
## 1
## Pre-emptive executive knowledgebase
## 1
## Pre-emptive neutral contingency
## 1
## Pre-emptive next generation Internet solution
## 1
## Pre-emptive next generation strategy
## 1
## Pre-emptive systematic budgetary management
## 1
## Pre-emptive transitional protocol
## 1
## Pre-emptive value-added workforce
## 1
## Pre-emptive well-modulated moderator
## 1
## Pre-emptive zero tolerance Local Area Network
## 1
## Proactive 5thgeneration frame
## 1
## Proactive actuating Graphical User Interface
## 1
## Proactive asymmetric definition
## 1
## Proactive bandwidth-monitored policy
## 1
## Proactive client-server productivity
## 1
## Proactive context-sensitive project
## 1
## Proactive encompassing paradigm
## 1
## Proactive interactive service-desk
## 1
## Proactive local focus group
## 1
## Proactive next generation knowledge user
## 1
## Proactive non-volatile encryption
## 1
## Proactive radical support
## 1
## Proactive secondary monitoring
## 1
## Profit-focused attitude-oriented task-force
## 1
## Profit-focused dedicated utilization
## 1
## Profit-focused secondary portal
## 1
## Profit-focused systemic support
## 1
## Profound bottom-line standardization
## 1
## Profound dynamic attitude
## 1
## Profound executive flexibility
## 1
## Profound explicit hardware
## 1
## Profound maximized workforce
## 1
## Profound optimizing utilization
## 1
## Profound stable product
## 1
## Profound well-modulated array
## 1
## Profound zero administration instruction set
## 1
## Programmable asymmetric data-warehouse
## 1
## Programmable didactic capacity
## 1
## Programmable empowering middleware
## 1
## Programmable empowering orchestration
## 1
## Programmable high-level benchmark
## 1
## Programmable uniform productivity
## 1
## Programmable uniform website
## 1
## Progressive 24/7 definition
## 1
## Progressive 24hour forecast
## 1
## Progressive analyzing attitude
## 1
## Progressive asynchronous adapter
## 1
## Progressive clear-thinking open architecture
## 1
## Progressive empowering alliance
## 1
## Progressive intermediate throughput
## 1
## Progressive non-volatile neural-net
## 1
## Progressive uniform budgetary management
## 1
## Public-key asynchronous matrix
## 1
## Public-key bi-directional Graphical User Interface
## 1
## Public-key disintermediate emulation
## 1
## Public-key foreground groupware
## 1
## Public-key impactful neural-net
## 1
## Public-key intangible Graphical User Interface
## 1
## Public-key mission-critical core
## 1
## Public-key non-volatile implementation
## 1
## Public-key real-time definition
## 1
## Public-key solution-oriented focus group
## 1
## Public-key zero-defect analyzer
## 1
## Quality-focused 5thgeneration orchestration
## 1
## Quality-focused bi-directional throughput
## 1
## Quality-focused hybrid frame
## 1
## Quality-focused maximized extranet
## 1
## Quality-focused optimizing parallelism
## 1
## Quality-focused scalable utilization
## 1
## Quality-focused zero-defect budgetary management
## 1
## Quality-focused zero-defect data-warehouse
## 1
## Quality-focused zero tolerance matrices
## 1
## Re-contextualized human-resource success
## 1
## Re-contextualized optimal service-desk
## 1
## Re-contextualized reciprocal interface
## 1
## Re-contextualized systemic time-frame
## 1
## Re-engineered composite moratorium
## 1
## Re-engineered context-sensitive knowledge user
## 1
## Re-engineered demand-driven capacity
## 1
## Re-engineered exuding frame
## 1
## Re-engineered impactful software
## 1
## Re-engineered intangible software
## 1
## Re-engineered neutral success
## 1
## Re-engineered non-volatile neural-net
## 1
## Re-engineered optimal policy
## 1
## Re-engineered real-time success
## 1
## Re-engineered responsive definition
## 1
## Re-engineered zero-defect open architecture
## 1
## Reactive bi-directional standardization
## 1
## Reactive bi-directional workforce
## 1
## Reactive composite project
## 1
## Reactive demand-driven capacity
## 1
## Reactive demand-driven strategy
## 1
## Reactive impactful challenge
## 1
## Reactive interactive protocol
## 1
## Reactive local challenge
## 1
## Reactive national success
## 1
## Reactive needs-based instruction set
## 1
## Reactive responsive emulation
## 1
## Reactive tangible contingency
## 1
## Reactive upward-trending migration
## 1
## Realigned 24/7 core
## 1
## Realigned content-based leverage
## 1
## Realigned global initiative
## 1
## Realigned intangible benchmark
## 1
## Realigned intermediate application
## 1
## Realigned next generation projection
## 1
## Realigned reciprocal framework
## 1
## Realigned scalable standardization
## 1
## Realigned systematic function
## 1
## Realigned tangible collaboration
## 1
## Realigned zero tolerance emulation
## 1
## Reduced background data-warehouse
## 1
## Reduced bi-directional strategy
## 1
## Reduced global support
## 1
## Reduced holistic help-desk
## 1
## Reduced incremental productivity
## 1
## Reduced mobile structure
## 1
## Reduced multimedia project
## 1
## Reverse-engineered 24hour hardware
## 1
## Reverse-engineered background Graphic Interface
## 1
## Reverse-engineered content-based intranet
## 1
## Reverse-engineered context-sensitive emulation
## 1
## Reverse-engineered dynamic function
## 1
## Reverse-engineered maximized focus group
## 1
## Reverse-engineered web-enabled support
## 1
## Reverse-engineered well-modulated capability
## 1
## Right-sized asynchronous website
## 1
## Right-sized logistical middleware
## 1
## Right-sized mobile initiative
## 1
## Right-sized multi-tasking solution
## 1
## Right-sized solution-oriented benchmark
## 1
## Right-sized system-worthy project
## 1
## Right-sized transitional parallelism
## 1
## Right-sized value-added initiative
## 1
## Robust context-sensitive neural-net
## 1
## Robust dedicated system engine
## 1
## Robust holistic application
## 1
## Robust logistical utilization
## 1
## Robust object-oriented Graphic Interface
## 1
## Robust responsive collaboration
## 1
## Robust transitional ability
## 1
## Robust uniform framework
## 1
## Robust web-enabled attitude
## 1
## Seamless 4thgeneration contingency
## 1
## Seamless bandwidth-monitored knowledge user
## 1
## Seamless cohesive conglomeration
## 1
## Seamless composite budgetary management
## 1
## Seamless full-range website
## 1
## Seamless holistic time-frame
## 1
## Seamless impactful info-mediaries
## 1
## Seamless intangible secured line
## 1
## Seamless motivating approach
## 1
## Seamless object-oriented structure
## 1
## Seamless optimal contingency
## 1
## Seamless real-time array
## 1
## Secured 24hour policy
## 1
## Secured clear-thinking middleware
## 1
## Secured encompassing Graphical User Interface
## 1
## Secured intermediate approach
## 1
## Secured scalable Graphical User Interface
## 1
## Secured secondary superstructure
## 1
## Secured uniform instruction set
## 1
## Secured upward-trending benchmark
## 1
## Self-enabling asynchronous knowledge user
## 1
## Self-enabling didactic pricing structure
## 1
## Self-enabling even-keeled methodology
## 1
## Self-enabling holistic process improvement
## 1
## Self-enabling incremental collaboration
## 1
## Self-enabling local strategy
## 1
## Self-enabling multimedia system engine
## 1
## Self-enabling optimal initiative
## 1
## Self-enabling tertiary challenge
## 1
## Self-enabling zero administration neural-net
## 1
## Sharable 5thgeneration access
## 1
## Sharable analyzing alliance
## 1
## Sharable bottom-line solution
## 1
## Sharable client-driven software
## 1
## Sharable dedicated Graphic Interface
## 1
## Sharable encompassing database
## 1
## Sharable grid-enabled matrix
## 1
## Sharable multimedia conglomeration
## 1
## Sharable optimal capacity
## 1
## Sharable reciprocal project
## 1
## Sharable secondary Graphical User Interface
## 1
## Sharable upward-trending support
## 1
## Sharable value-added solution
## 1
## Stand-alone background open system
## 1
## Stand-alone eco-centric system engine
## 1
## Stand-alone empowering benchmark
## 1
## Stand-alone encompassing throughput
## 1
## Stand-alone explicit orchestration
## 1
## Stand-alone logistical service-desk
## 1
## Stand-alone motivating moratorium
## 1
## Stand-alone national attitude
## 1
## Stand-alone radical throughput
## 1
## Stand-alone reciprocal synergy
## 1
## Stand-alone tangible moderator
## 1
## Stand-alone well-modulated product
## 1
## Streamlined analyzing initiative
## 1
## Streamlined cohesive conglomeration
## 1
## Streamlined exuding adapter
## 1
## Streamlined homogeneous analyzer
## 1
## Streamlined logistical secured line
## 1
## Streamlined next generation implementation
## 1
## Streamlined non-volatile analyzer
## 1
## Switchable 3rdgeneration hub
## 1
## Switchable analyzing encryption
## 1
## Switchable mobile framework
## 1
## Switchable multi-state success
## 1
## Switchable real-time product
## 1
## Switchable secondary ability
## 1
## Switchable well-modulated infrastructure
## 1
## Synchronized dedicated service-desk
## 1
## Synchronized full-range portal
## 1
## Synchronized grid-enabled moratorium
## 1
## Synchronized human-resource moderator
## 1
## Synchronized leadingedge help-desk
## 1
## Synchronized multi-tasking ability
## 1
## Synchronized multimedia model
## 1
## Synchronized national infrastructure
## 1
## Synchronized stable complexity
## 1
## Synchronized systemic hierarchy
## 1
## Synchronized user-facing core
## 1
## Synchronized zero tolerance product
## 1
## Synergistic asynchronous superstructure
## 1
## Synergistic discrete middleware
## 1
## Synergistic dynamic orchestration
## 1
## Synergistic fresh-thinking array
## 1
## Synergistic non-volatile analyzer
## 1
## Synergistic reciprocal attitude
## 1
## Synergistic stable infrastructure
## 1
## Synergistic value-added extranet
## 1
## Synergized clear-thinking protocol
## 1
## Synergized coherent interface
## 1
## Synergized cohesive array
## 1
## Synergized context-sensitive database
## 1
## Synergized grid-enabled framework
## 1
## Synergized hybrid time-frame
## 1
## Synergized intangible open system
## 1
## Synergized multimedia emulation
## 1
## Synergized uniform hierarchy
## 1
## Synergized well-modulated Graphical User Interface
## 1
## Team-oriented 6thgeneration extranet
## 1
## Team-oriented bi-directional secured line
## 1
## Team-oriented context-sensitive installation
## 1
## Team-oriented dynamic forecast
## 1
## Team-oriented encompassing portal
## 1
## Team-oriented executive core
## 1
## Team-oriented grid-enabled Local Area Network
## 1
## Team-oriented high-level orchestration
## 1
## Team-oriented systematic installation
## 1
## Team-oriented transitional methodology
## 1
## Team-oriented zero-defect initiative
## 1
## Total 5thgeneration encoding
## 1
## Total 5thgeneration standardization
## 1
## Total asynchronous architecture
## 1
## Total bi-directional success
## 1
## Total coherent archive
## 1
## Total coherent superstructure
## 1
## Total cohesive moratorium
## 1
## Total directional approach
## 1
## Total even-keeled architecture
## 1
## Total grid-enabled application
## 1
## Total human-resource flexibility
## 1
## Total local synergy
## 1
## Total user-facing hierarchy
## 1
## Total zero administration software
## 1
## Triple-buffered 3rdgeneration migration
## 1
## Triple-buffered demand-driven alliance
## 1
## Triple-buffered foreground encryption
## 1
## Triple-buffered high-level Internet solution
## 1
## Triple-buffered human-resource complexity
## 1
## Triple-buffered multi-state complexity
## 1
## Triple-buffered needs-based Local Area Network
## 1
## Triple-buffered reciprocal time-frame
## 1
## Triple-buffered regional toolset
## 1
## Triple-buffered scalable groupware
## 1
## Triple-buffered systematic info-mediaries
## 1
## Universal 24/7 implementation
## 1
## Universal asymmetric archive
## 1
## Universal asymmetric workforce
## 1
## Universal bi-directional extranet
## 1
## Universal contextually-based system engine
## 1
## Universal empowering adapter
## 1
## Universal even-keeled analyzer
## 1
## Universal global intranet
## 1
## Universal incremental array
## 1
## Universal multi-state system engine
## 1
## Universal transitional Graphical User Interface
## 1
## Up-sized 6thgeneration moratorium
## 1
## Up-sized asymmetric firmware
## 1
## Up-sized bi-directional infrastructure
## 1
## Up-sized bifurcated capability
## 1
## Up-sized executive moderator
## 1
## Up-sized incremental encryption
## 1
## Up-sized intangible circuit
## 1
## Up-sized maximized model
## 1
## Up-sized next generation architecture
## 1
## Up-sized real-time methodology
## 1
## Up-sized secondary software
## 1
## Up-sized tertiary contingency
## 1
## Upgradable 4thgeneration portal
## 1
## Upgradable asymmetric emulation
## 1
## Upgradable asynchronous circuit
## 1
## Upgradable directional system engine
## 1
## Upgradable even-keeled challenge
## 1
## Upgradable even-keeled hardware
## 1
## Upgradable heuristic system engine
## 1
## Upgradable local migration
## 1
## Upgradable logistical flexibility
## 1
## Upgradable multi-tasking initiative
## 1
## Upgradable optimizing toolset
## 1
## Upgradable system-worthy array
## 1
## User-centric attitude-oriented adapter
## 1
## User-centric composite contingency
## 1
## User-centric discrete success
## 1
## User-centric intangible contingency
## 1
## User-centric intangible task-force
## 1
## User-centric intermediate knowledge user
## 1
## User-centric solution-oriented emulation
## 1
## User-friendly asymmetric info-mediaries
## 1
## User-friendly bandwidth-monitored attitude
## 1
## User-friendly client-server instruction set
## 1
## User-friendly content-based customer loyalty
## 1
## User-friendly grid-enabled analyzer
## 1
## User-friendly impactful time-frame
## 1
## User-friendly upward-trending intranet
## 1
## User-friendly well-modulated leverage
## 1
## Versatile 4thgeneration system engine
## 1
## Versatile 6thgeneration parallelism
## 1
## Versatile content-based protocol
## 1
## Versatile dedicated software
## 1
## Versatile homogeneous capacity
## 1
## Versatile local forecast
## 1
## Versatile mission-critical application
## 1
## Versatile next generation pricing structure
## 1
## Versatile optimizing projection
## 1
## Versatile reciprocal structure
## 1
## Versatile responsive knowledge user
## 1
## Versatile scalable encryption
## 1
## Versatile solution-oriented secured line
## 1
## Versatile transitional monitoring
## 1
## Virtual 5thgeneration emulation
## 1
## Virtual 5thgeneration neural-net
## 1
## Virtual bandwidth-monitored initiative
## 1
## Virtual bifurcated portal
## 1
## Virtual composite model
## 1
## Virtual context-sensitive support
## 1
## Virtual executive implementation
## 1
## Virtual homogeneous budgetary management
## 1
## Virtual impactful algorithm
## 1
## Virtual scalable secured line
## 1
## Vision-oriented asynchronous Internet solution
## 1
## Vision-oriented attitude-oriented Internet solution
## 1
## Vision-oriented bifurcated contingency
## 1
## Vision-oriented contextually-based extranet
## 1
## Vision-oriented human-resource synergy
## 1
## Vision-oriented methodical support
## 1
## Vision-oriented multi-tasking success
## 1
## Vision-oriented next generation solution
## 1
## Vision-oriented optimizing middleware
## 1
## Vision-oriented real-time framework
## 1
## Vision-oriented system-worthy forecast
## 1
## Vision-oriented uniform knowledgebase
## 1
## Visionary analyzing structure
## 1
## Visionary asymmetric encryption
## 1
## Visionary client-driven installation
## 1
## Visionary maximized process improvement
## 1
## Visionary mission-critical application
## 1
## Visionary multi-tasking alliance
## 1
## Visionary reciprocal circuit
## 16.0 Bivariate and Multivariate Analysis
This looks at the relation between 2 or more variable.
we will handle covariance,correlation coefficient, and scatter plots
###6.1 covariance between age and the daily time spent on site
#Checking the covariance between age and the daily time spent on site
#
## Assigning the Age column to the variable Age
Age<-my_dataset$Age
#
#assigning Daily.Time.Spent.on.Site colunm to variable DTSS
DTSS<-my_dataset$Daily.Time.Spent.on.Site
#
#Using the cov() function to determine the covariance
cov(Age,DTSS)## [1] -46.17415observation, The covariance of Age and Daily.Time.Spent.on.Site variable is about -46.175,It indicates a negative linear relationship between the two variables
###6.2 covariance between age and Daily.Internet.Usage
#Checking the covariance between age and the daily time spent on site
#
## Assigning the Age column to the variable Age
Age<-my_dataset$Age
#
#assigning Daily.Internet.Usage colunm to variable DIU
DIU<-my_dataset$Daily.Internet.Usage
#
#Using the cov() function to determine the covariance
cov(Age,DIU)## [1] -141.6348observation. The covariance of Age and Daily.Internet.Usage variable is about -141.635, It indicates a negative linear relationship between the two variables
###6.3 covariance between age and Area Income
#Checking the covariance between age and the daily time spent on site
#
## Assigning the Age column to the variable Age
Age<-my_dataset$Age
#
#assigning Area Income colunm to variable income
income<-my_dataset$Area.Income
#
#Using the cov() function to determine the covariance
cov(Age,income)## [1] -21520.93observation: The covariance of Age and Daily.Internet.Usage variable is about -21520.93, It indicates a negative linear relationship between the two variables
###6.4 covariance between Daily Time Spent on Site and the Daily Internet Usage
#Using the cov() function to determine the covariance
cov(DTSS, DIU)## [1] 360.9919observation: The higher the Daily Time Spent on Site the higher the Daily Internet Usage-Positive Covariance
###6.5 covariance between gender and Clicked.on.Ad
#Using the cov() function to determine the covariance
cov(Gender,Clicked)## [1] -0.00950951###6.6 covariance between Clicked.on.Ad and age
#Using the cov() function to determine the covariance
cov(Clicked,Age)## [1] 2.164665###6.7 covariance between Clicked.on.Ad and Daily.Time.Spent.on.Site
#Using the cov() function to determine the covariance
cov(Clicked,DTSS)## [1] -5.933143###6.8 covariance between Clicked.on.Ad and Daily.Internet.Usage
#Using the cov() function to determine the covariance
cov(Clicked,DIU)## [1] -17.27409###6.9 covariance between Clicked.on.Ad and Area income
#Using the cov() function to determine the covariance
cov(Clicked,income)## [1] -3195.989###6.9 covariance for numerical colunms
#Using the cov() function to determine the covariance
cov(Numeric)## Daily.Time.Spent.on.Site Age Area.Income
## Daily.Time.Spent.on.Site 251.3370949 -4.617415e+01 6.613081e+04
## Age -46.1741459 7.718611e+01 -2.152093e+04
## Area.Income 66130.8109082 -2.152093e+04 1.799524e+08
## Daily.Internet.Usage 360.9918827 -1.416348e+02 1.987625e+05
## Male -0.1501864 -9.242142e-02 8.867509e+00
## Clicked.on.Ad -5.9331431 2.164665e+00 -3.195989e+03
## Daily.Internet.Usage Male Clicked.on.Ad
## Daily.Time.Spent.on.Site 3.609919e+02 -0.15018639 -5.933143e+00
## Age -1.416348e+02 -0.09242142 2.164665e+00
## Area.Income 1.987625e+05 8.86750903 -3.195989e+03
## Daily.Internet.Usage 1.927415e+03 0.61476667 -1.727409e+01
## Male 6.147667e-01 0.24988889 -9.509510e-03
## Clicked.on.Ad -1.727409e+01 -0.00950951 2.502503e-01observations:
There are positive covariances between the following variables
1.Area Income and Daily Time Spent on Site
2.Age and Clicking on the Advert.
3.Area Income and Daily Internet Usage.
4.Area Income and Male
5.Daily Internet Usage and Daily Time Spent on Site
6.Male and Daily Internet Usage
7.Clicked on Advert and Age
The rest of the variables exhibit negative Covariances.
7.0 Correlation
7.1 correlation between age and Daily Time Spent on Site
cor(Age,DTSS)## [1] -0.33151337.2 correlation between age and Daily Internet Usage
cor(Age,DIU)## [1] -0.36720867.3 correlation between age and income
cor(Age,income)## [1] -0.1826057.4 correlation between age and Clicked on Advert
cor(Age,Clicked)## [1] 0.49253137.5 correlation between Daily Time Spent on Site and Daily Internet Usage
cor(DTSS,DIU)## [1] 0.51865857.6 correlation between Gender and Clicked on Advert
cor(Gender,Clicked)## [1] -0.038027477.7 correlation between Gender and Daily Time Spent on Site
cor(Gender,DTSS)## [1] -0.018950857.8 correlation between Gender and Daily internet usage
cor(Gender,DIU)## [1] 0.028012337.9 correlation between Clicked on Advert and area income
cor(Clicked,income)## [1] -0.4762546###7.10 correlation for numerical colunms
#Using the cov() function to determine the covariance
cor(Numeric)## Daily.Time.Spent.on.Site Age Area.Income
## Daily.Time.Spent.on.Site 1.00000000 -0.33151334 0.310954413
## Age -0.33151334 1.00000000 -0.182604955
## Area.Income 0.31095441 -0.18260496 1.000000000
## Daily.Internet.Usage 0.51865848 -0.36720856 0.337495533
## Male -0.01895085 -0.02104406 0.001322359
## Clicked.on.Ad -0.74811656 0.49253127 -0.476254628
## Daily.Internet.Usage Male Clicked.on.Ad
## Daily.Time.Spent.on.Site 0.51865848 -0.018950855 -0.74811656
## Age -0.36720856 -0.021044064 0.49253127
## Area.Income 0.33749553 0.001322359 -0.47625463
## Daily.Internet.Usage 1.00000000 0.028012326 -0.78653918
## Male 0.02801233 1.000000000 -0.03802747
## Clicked.on.Ad -0.78653918 -0.038027466 1.00000000Observations:
There are negative correlations between the following variables 1.Area Income and Daily Time Spent on Site 2.Male and Daily Time Spent on Site 3.Clicking on the Advert and Daily Time Spent on Site. 4.Area Income and Age 5.Daily Internet Usage and Age 6.Male and Age 7.Area Income and Age 8.Area Income and Clicking on the Advert 9.Daily Internet usage and Clicking on the advert. 10.Male and Clicking on the Advert
There are positive Correlations between the following variables: 1.Age and Clicking on the advert 2.Male and Daily Internet Usage 3.Male and Area Income 4.Daily Time Spent on Site and Daily Internet Usage. 5.Area Income and Daily Time Spent on Site 6.Area Income and Daily Internet Usage 7.Area Income and Male 8.Age and Clicking on the Advert.
8.0 scatter plots
###8.1 age and time spend on the site variable scatter plot
#Using the plot() function to determine the relation
#
plot(Age, DTSS, xlab="Age of the Individual", ylab="Time spent on the site")
###8.2 age and Daily internate usage scatter plot
#Using the plot() function to determine the relation
#
plot(Age, DIU, xlab="Age of the Individual", ylab="Internet Usage")
###8.3 age and area income variable scatter plot
#Using the plot() function to determine the relation
#
plot(Age, income, xlab="Age of the Individual", ylab="Area Income")
###8.4 age and clicked on advert variable scatter plot
#Using the plot() function to determine the relation
#
plot(Age, Clicked, xlab="Age of the Individual", ylab="Clicked on the Ad")
###8.5 gender and area income variable scatter plot
#Using the plot() function to determine the relation
#
plot(Gender, income, xlab="Gender of the Individual", ylab="Area Income")
###8.6 gender and daily internet usage variable scatter plot
#Using the plot() function to determine the relation
#
plot(Gender, DIU, xlab="Gender of the Individual", ylab="Internet Usage")
###8.7 gender and daily time spent on site variable scatter plot
#Using the plot() function to determine the relation
#
plot(Gender, DTSS, xlab="Gender of the Individual", ylab="Time Spent on Site")
###8.8 income and daily internet usage variable scatter plot
#Using the plot() function to determine the relation
#
plot(income, DIU, xlab="Income of the Area", ylab="Internet Usage")
###8.9 income and daily time spent on site variable scatter plot
#Using the plot() function to determine the relation
#
plot(income, DTSS, xlab="Income of the Area", ylab="Time Spent on Site")
## 9.0 observations:
The data was clean and complete i.e. contained no outliers and no missing values.
The modal age was 31 years and the range was between 19 and 61.
Most of the individuals spent around 62.26 Minutes on the site.The time ranged from 32.60 minutes to 91.43.
The Average Area Income of the individuals was 55,000 which ranged between 13,996.5 and 79,484.80
The Daily Internet Usage had an average of 180 Mbs and ranged between 104.78 and 269.96
The most frequent cities were; Lake Faith and West Ryan
The most frequent Countries were; Turkey and Australia.
There were positive covariances between the following variables 1.Area Income and Daily Time Spent on Site 2.Age and Clicking on the Advert. 3.Area Income and Daily Internet Usage. 4.Area Income and Male 5.Daily Internet Usage and Daily Time Spent on Site 6.Male and Daily Internet Usage 7.Clicked on Advert and Age
The rest of the variables exhibit negative Covariances.
The number of females was more than that of male counterparts.
The number of individuals who clicked on the advert and those who didn’t were equal at 500.
There are negative correlations between the following variables 1.Area Income and Daily Time Spent on Site 2.Male and Daily Time Spent on Site 3.Clicking on the Advert and Daily Time Spent on Site. 4.Area Income and Age 5.Daily Internet Usage and Age 6.Male and Age 7.Area Income and Age 8.Area Income and Clicking on the Advert 9.Daily Internet usage and Clicking on the advert. 10.Male and Clicking on the Advert
There were positive Correlations between the following variables: 1.Age and Clicking on the advert 2.Male and Daily Internet Usage 3.Male and Area Income 4.Daily Time Spent on Site and Daily Internet Usage. 5.Area Income and Daily Time Spent on Site 6.Area Income and Daily Internet Usage 7.Area Income and Male 8.Age and Clicking on the Advert.
10.0 Conclusion
After analysis, we conclude that following characteristics would help identify an individual who would click on the ad:
Daily Time Spent on Site-the higher the time the lower the chances of clicking.
Age-The higher the Age the Higher the chances.
Area Income-The lower the income the higher the chances.
Internet Usage-The lower the Internet Usage the higher the chances.
10.1 Recommendation
It was hard to analyze the Ad Topic Line column as it had various different themes. for effective analysis, the major themes should be identified and used on the rest.
11.0 Follow up questions
11. 1 Did we have the right data?
Yes
11.2 Do we need other data to answer our question?
No
11.3 Did we have the right question?
yes