Learn How To Use All 3 Types of ANOVA Built Into Excel To Improve Your Internet Marketing. Learn How To Conduct the Market Tests, Input the Data Into Excel, Run All 3 Types of ANOVA, and How To Interpret the Excel Output For Each ANOVA Types. You'll Become an ANOVA - Excel Master !

1. How To Use All 3 Types of ANOVA Built Into Excel To Make Your Internet Marketing More Effective http:// blog.excelmasterseries.com /

2. What Is ANOVA? ● ANOVA stands for “Analysis of Variance” ● ANOVA tells whether varying an element effected the output ● Marketers use ANOVA to find out whether changing an element of a marketing campaign had an effect http:// blog.excelmasterseries.com /

3. The 3 Types of ANOVA Built Into Excel 1) Single-Factor ANOVA 2) Two-Factor ANOVA Without Replication 3) Two-Factor ANOVA With Replication http:// blog.excelmasterseries.com /

4. Single-Factor ANOVA Tests Only 1 Input Element ● Single-Factor ANOVA tests the Null Hypothesis for that factor, which states that varying the factor does not affect the outcome ● An underlying assumption for all ANOVA tests is that no other factors vary except the ones being tested http:// blog.excelmasterseries.com /

5. Single-Factor ANOVA Test Data Ready for Input to Excel ● Yellow highlighted cells are the input range for Excel http:// blog.excelmasterseries.com /

6. Single-Factor ANOVA Excel Output http:// blog.excelmasterseries.com /

7. Two-Factor ANOVA Without Replication Tests 2 Input Elements ● Two-Factor ANOVA Without Replication tests the Null Hypothesis for each factor, which states that varying the factor does not affect the outcome http:// blog.excelmasterseries.com /

8. Two-Factor ANOVA Without Replication Test Data Ready for Input to Excel ● Yellow highlighted cells are the input range for Excel http:// blog.excelmasterseries.com /

9. Two-Factor ANOVA Without Replication Excel Output http:// blog.excelmasterseries.com /

10. Two-Factor ANOVA With Replication Tests 2 Input Elements and the Interaction Between the 2 Elements ● Two-Factor ANOVA With Replication replicates the Two-Factor Test in 2 places in order to test the interaction between the 2 factors ● Two-Factor ANOVA With Replication tests the Null Hypothesis for each factor, which states that varying the factor does not affect the outcome. The interaction has its own Null Hypothesis which is tested which states that Interaction has no effect.

11. Two-Factor ANOVA With Replication Test Data Ready for Input to Excel ● Yellow highlighted cells are the input range for Excel http:// blog.excelmasterseries.com /

12. Two-Factor ANOVA With Replication Excel Output http:// blog.excelmasterseries.com /

13. Summary of ANOVA That Was Run 1) Create 5 sets of Ad Text for 1 Ad Group 2) Create 3 sets of Headlines for that Ad Group 3) Run all 15 Ad Text / Headline Combinations 4) Prepare test results for input into Excel ANOVA 5) Run all 3 types of ANOVA on the test results 6) Evaluate the output for each Excel ANOVA http:// blog.excelmasterseries.com /

14. Single-Factor ANOVA Excel Output http:// blog.excelmasterseries.com /

15. Interpretation of Single-Factor ANOVA Excel Output ● Headlines P Value (0.0013) less than Alpha (0.05) we are 95% certain that varying Headline affects output http:// blog.excelmasterseries.com /

16. Two-Factor ANOVA Without Replication Excel Output http:// blog.excelmasterseries.com /

17. Interpretation of Two-Factor ANOVA Without Replication Excel Output ● Headlines P Value (0.0005) less than Alpha (0.05) we are 95% certain that varying Headline affects output ● Headlines P Value (0.627) greater than Alpha (0.05) we are not 95% certain that varying Headline affects output http:// blog.excelmasterseries.com /

18. Two-Factor ANOVA With Replication Excel Output http:// blog.excelmasterseries.com /

19. Interpretation of Two-Factor ANOVA With Replication Excel Output ● Headlines P Value (1.18 E06) less than Alpha (0.05) we are 95% certain that varying Headline affects output ● Ad Text P Value (0.1568) greater than Alpha (0.05) we are not 95% certain that varying Ad Text affects output ● Interaction P Value (0.0402) less than Alpha (0.05) we are 95% certain that varying Interaction affects output http:// blog.excelmasterseries.com /