# Two Way ANOVA (Analysis of Variance) With Replication

## You Don't Have to be a Statistician to Conduct Two Way ANOVA Tests

Two-Way ANOVA (ANalysis Of Variance) , also known as two-factor ANOVA, can help you determine if two or more samples have the same "mean" or average. Note: Your data must be normal to use ANOVA.

### QI Macros Excel Add-in Makes Two Way ANOVA a Snap

• Installs a new tab on Excel's menu.
• Performs the calculations and interprets the results for you. Results indicate:
• Reject or Cannot Reject the Null Hypothesis
• Means are the Same or Means are Different

### Two-Way ANOVA Test With Replication Example

What if you have two populations of patients (male/female) and three different kinds of medications, and you want to evaluate their effectiveness? You might run a study with three "replications", three men and three women.

#### To Conduct the Anova Test in Excel Using QI Macros:

1. Click and drag over your data to select it:
2. Click on QI Macros Menu, Statistical Tools and then ANOVA Two Factor with Replication:
3. QI Macros will prompt you for how many rows are in each sample (three) and for a significance level. Default is alpha=0.05 for a 95% confidence.
4. QI Macros will perform all of the calculations and interpret the results for you:

### Interpretation of the Two Way ANOVA Results

QI Macros built in code compares the p-values (0.179) to the signficance level (0.05) and tells you: "Cannot Reject the Null Hypothesis because p>0.05" and that the "Means are the same".

### Tips on Setting Up Your Data for Two-Factor with Replication

To analyze data, Excel requires you to set the data up in a way that can be analyzed.

The example below shows how to set up the data for two categories of patients treated with three different drugs:

Then, if you're just interested in the single factor DRUGS, select and run a ANOVA single factor on the three drug columns:

If you're interested in a ANOVA two-factor analysis (patients vs drugs), select and run a two-factor analysis with repetition (more than one patient in the category receives the same drug).

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