<<< Click here go one step back
Two way ANOVA test
Suppose we have two factors ( 2 categorical variable), we can test them together along with their interaction.
Let us understand it by the same example ( One way ANOVA). In the data, there are three variables :
1. Sales value of XYZ category
2. Media Spend as High, Medium and Low ( based on how many $ were spent on promotion)
3. Festive Season Flag ( Yes or No)
Now suppose, we have a hypothesis that Sales is independent of media spend and Festivity.
So the null hypothesis is equality of means:
H0 : Mean sales is same across categories
H1 : Mean sales of at least one category is significantly different
Proc anova data = a.sales;
Class Media_Spend Festive_season ;
Model Sales = Media_Spend Festive_season Media_Spend * Festive_season ;
Run;
Quit;
As the p value is < 0.01in case of Media Spend, Festive_Season and their interaction as well, it means:
1. Mean of Sales across Media Spend brackets is different
2. Mean of sales in Festive and Non Festive season is different
3. Considering categories with both Media Spend and Festive Season, Sales is different across the categories. Even their interaction is significant.
Just one thing : When interactions are present, the main effects of the independent variables don't have their usual interpretations.
Enjoy reading our other articles and stay tuned with ...
Kindly do provide your feedback in the 'Comments' Section and share as much as possible.
No comments:
Post a Comment
Do provide us your feedback, it would help us serve your better.