Assessing Pearson assumptions

For a Pearson correlation to be appropriate, the data must follow two assumptions: linearity and normally distributed.

A company is interested in running a Pearson correlation on the amount of time spent on a website and the amount of money spent purchasing items on the website, first assessing the correlation ignoring groups. Assess whether a Pearson correlation is appropriate given the linear and normal distribution assumptions that must be met.

The ggplot2 package and SiteSales dataset have been loaded for you.

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A/B Testing in R

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Instructions

Create a scatter plot with AmountSpent on the x-axis and TimeSearching on the y-axis to assess the linearity of the relationship.
Use shapiro.test() to determine whether AmountSpent is normally distributed.
Use shapiro.test() to determine whether TimeSearching is normally distributed.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Assess the assumption of linearity
ggplot(___) +
  ___

# Assess the normality of the `AmountSpent` variable
___

# Assess the normality of the `TimeSearching` variable
___

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