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Note: this analysis was performed using the open source software R and Rstudio.

Objective

The objective of this tutorial is to explain how bivariate analysis works.This analysis can be used by marketers to make decisions about their pricing strategies, advertising strategies, and promotion stratgies among others.

Bivariate analysis is one of the simplest forms of statistical analysis. It is generally used to find out if there is a relationship between two sets of values (or two variables). That said, it usually involves the variables X and Y (statisticshowto.com).

Dataset - We will be using two online datasets available in R for this tutorial

plot(y3 ~ x2, data = anscombe, pch = 16)
abline(lm(y3 ~ x3, anscombe), col = "grey20")

### Question 1:is there a relationship between x and y? If so, how does the relationship look like? ## Yes there is a relationship. You can see that both x and y are growing together.

library(readr)
library(readr)
ad_sales <- read_csv('https://raw.githubusercontent.com/utjimmyx/regression/master/advertising.csv')
## ! curl package not installed, falling back to using `url()`
## Warning: Missing column names filled in: 'X1' [1]
## Warning: Duplicated column names deduplicated: 'X1' => 'X1_1' [2]
## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   X1 = col_double(),
##   X1_1 = col_double(),
##   TV = col_double(),
##   radio = col_double(),
##   newspaper = col_double(),
##   sales = col_double()
## )
plot(sales ~ TV, data = ad_sales)

Question 2:Is there a relationship between TV advertising and Sales? If so, how does the relationship look like?

Yes there is a relationship. You can see that the more ads there are that the higher the sales are.

Question 3:Can you plot the relationship between radio advertising and Sales? If so, how does the relationship look like?

###As you can see below, you can see a slight growth together, but it is not as consolidated together as TV ads with sales.

library(readr)
library(readr)
ad_sales <- read_csv('https://raw.githubusercontent.com/utjimmyx/regression/master/advertising.csv')
## ! curl package not installed, falling back to using `url()`
## Warning: Missing column names filled in: 'X1' [1]
## Warning: Duplicated column names deduplicated: 'X1' => 'X1_1' [2]
## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   X1 = col_double(),
##   X1_1 = col_double(),
##   TV = col_double(),
##   radio = col_double(),
##   newspaper = col_double(),
##   sales = col_double()
## )
plot(sales ~ radio, data = ad_sales)

###Question 4:Three things you learned from this tutorial ###I learned about bivariate, multivariate, and univariate analysis. I also learned how to plot the relationship between two vairables. Lastly, I learned how to use RStudio Cloud better.

References

Bivariate Analysis Definition & Example https://www.statisticshowto.com/bivariate-analysis/#:~:text=Bivariate%20analysis%20means%20the%20analysis,the%20variables%20X%20and%20Y.

https://www.sciencedirect.com/topics/mathematics/bivariate-data