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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.

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, what does the relationship look like?

There is a relationship between x and y. The graph looks like a positive relationship.

library(readr)
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)

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

Yes, there is a positive relationship between TV advertising and Sales.

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

Question 4: Explain one of the functions you learned in your own words.

I learned the function Plot (). It showed me how to insert a graph into the function.

plot(sales ~ radio, data = ad_sales)