In: Statistics and Probability
We want to compare males and females (gender) based on the difference in time spent on social media (measured as hours per day)
- One variable is categorical, other is numeric and there are two categories, hence we will use t-test
We want to compare our customers and the customers of our closest competitors based on their brand loyalty (measured as a Likert scale from 1 to 5)
- One variable is categorical, other is numeric and there are more than two categories, hence we will use ANOVA
We want to compare resident and commuter students based on differences in their gender (males and females)
- Both the variables are categorical, hence we will use chi square
We want to compare freshmen, sophomores, juniors, and seniors based on differences in time spent studying (hours per day)
- One variable is categorical, other is numeric and there are more than two categories, hence we will use ANOVA
We want to compare freshmen, sophomores, juniors, and seniors based on their willingness to recommend their school (simply measured as Yes/No).
- Both the variables are categorical, hence we will use chi square
We want to compare males and females based on their consumption of sugary drinks (ounces per day).
- One variable is categorical, other is numeric and there are two categories, hence we will use t-test