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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 strategies 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")
### Question 1:is there a relationship between x and y? If so, how does the relationship look like? ## Yes, there is a positive relationship between x and y.
library(readr)
library(readr)
ad_sales <- read_csv('https://raw.githubusercontent.com/utjimmyx/regression/master/advertising.csv')
## 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)
Yes, there is a positive relationship between TV advertising and Sales. The more you invest into TV advertising, the higher your sales will be.
There is a somewhat positive relationship between radio advertising and sales.
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