Bivariate analysis for marketing managers

install.packages("tidyverse")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)

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 explanatory analysis.

library(ggplot2)
head(ad_sales)

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 explantory analysis.

#Question 1

There is a relationship between x and y. The relationship looks linear.

#Question 2

A coefficient represents the change in a n dependent variable for a unit change in an independent variable. There is a positive relationship between TV advertising and sales which means as TV ads spending increases the sales increase as well.

#Question 3

The equation of a simple linear regression depicts a dependency relationship between two variables or two sets of variables.

#Question 4

library(ggplot2)

ggplot(ad_sales,aes(x = radio, y = sales)) + 
  geom_point(colorr= "blue") +
  geom_smooth(method = "Im", colorr = "red" )+
  labs( title = " Sales vs. Radio Advertising", 
        x = "Radio Advertsing Budget",
        y = "Sales") + 
  theme_minimal()

## Warning in geom_point(colorr = "blue"): Ignoring unknown parameters: `colourr`

## Warning in geom_smooth(method = "Im", colorr = "red"): Ignoring unknown
## parameters: `colourr`

## `geom_smooth()` using formula = 'y ~ x'

## Warning: Failed to fit group -1.
## Caused by error in `compute_group()`:
## ! object 'weight' not found

#Question 5