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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).
plot(y3 ~ x2, data = anscombe, pch = 16)
abline(lm(y3 ~ x3, anscombe), col = "grey20")
Yes there is a positive linear 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)
Yes there is a positive linear relationship as well. The data is more of a positive cluster than a straight line.
plot(sales ~ radio, data = ad_sales)
###Your answer here - There is no relationship between radio advertising and sales. Just a cluster of data.
One of the functions I learned was how to create a graph between two different variables.
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