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

library(readr)
ad_sales <- read_csv('https://raw.githubusercontent.com/utjimmyx/regression/master/advertising.csv')
## New names:
## Rows: 200 Columns: 6
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," dbl
## (6): ...1, X1, TV, radio, newspaper, sales
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...1`
plot(sales ~ TV, data = ad_sales)

plot(sales ~ radio, data = ad_sales)

This is the end of part 1 for my exploratory analysis.

library(ggplot2)
head(ad_sales)
## # A tibble: 6 × 6
##    ...1    X1    TV radio newspaper sales
##   <dbl> <dbl> <dbl> <dbl>     <dbl> <dbl>
## 1     1     1 230.   37.8      69.2  22.1
## 2     2     2  44.5  39.3      45.1  10.4
## 3     3     3  17.2  45.9      69.3   9.3
## 4     4     4 152.   41.3      58.5  18.5
## 5     5     5 181.   10.8      58.4  12.9
## 6     6     6   8.7  48.9      75     7.2
ggplot(data = ad_sales, aes(x = TV))+
  geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

This is the end of part 2 for my exploratory analysis

#Question 1 1. The relationship between x and y are TV/Radio and sales. TV/Radio is x and Sales is Y.

#Question 2 2. The definition of a coefficient is a numerical or constant quantity placed before and multiplying the variable in an algebraic expression. There is a relationship between TV advertising and sales, because as seen in the chart as TV advertisement goes up sales goes up. This is an example of an increasing function.

#Question 3 3. We can address questions under sales prediction and customer behavior through the graph. Some limitations may be single variable dependency which means just because two things alien doesn’t mean they factor off each other.

#Question 4 4. Yes, as seen above. The relationship is constantly increasing.

#Question 5 5. Refer to the histogram above.