The differences we see in our samples might be the result of random sampling error.

However, we need to determine whether our data support the notion that the population means are not equal. The Summary table indicates that the mean strengths range from a low of 8.837952 for supplier 4 to a high of 11.20252 for supplier 1. Change this value only when you have a specific reason for doing so.Īfter Excel creates the output, I autofit the width of column A to display all of the text in it. Excel uses a default Alpha value of 0.05, which is usually a good value.Ensure that you include the label row in step #3. This option helps make the output easier to interpret. Check the Labels checkbox if you have meaningful variables labels in row 1.Under Input, select the ranges for all columns of data.From the Data Analysis popup, choose Anova: Single Factor.Download the CSV dataset for this example: OneWayANOVAExcel. For our example, each column represents raw material from one supplier. To perform a one-way ANOVA in Excel, arrange your data in columns, as shown below. Now, we want to determine whether the mean strengths of the material from the four suppliers are different. We draw a random sample of 10 units of material from each supplier and measure the strength of all units. Supplier is our categorical independent variable (factor) while strength is the continuous dependent variable. Let’s conduct a one-way ANOVA! Our example scenario is that we are comparing the strength of raw material from four suppliers. Step-by-Step Instructions for Running a One Factor ANOVA in Excel Also, learn about the difference between descriptive statistics and inferential statistics and learn more about interpreting p-values.

Sigmaplot 11 do not test bonferroni