This week, we are studying analysis of variance, commonly called


This week, we are studying Analysis of Variance, commonly called ANOVA. ANOVA is used the compare the mean of a dependent variable associated with the effect of at least three independent variables. For example, we could study the mean sodium amount in condiments, desserts, and cereal. In this case, the dependent variable is the amount of sodium and the independent variables are condiments, desserts, and cereal.  Note: The hypothesis test using ANOVA will tell you if the mean is the same for the samples but does not tell you which is different. 

To prepare for this Discussion:

  • Review the following resources:

Discussion Resources (click to expand/reduce)

  • To do this week’s Discussion, you will need to have data involving at least three qualitative variables. You may want to start over with a new data set, as shown in the example below.

Example: (click to expand/reduce)

  • Review the rubric that will be used for grading.

With these thoughts in mind:

By Day 1

By the end of Day 1, you can post your scenario and data for your Instructor to review.  If you do not submit this by the end of Day 1, you will need to proceed to submit the entire Discussion on Day 3.

By Day 3

Write 1–2 paragraphs that include the following:

  1. Describe your scenario and provide your dataset.
  2. State your null and alternative hypotheses. Be sure to state your chosen level of significance.
  3. Enter your data into the Sample Editor in Statdisk.  Choose Analysis, One-Way Analysis of Variance.
  4. Perform the test and state your conclusion. Remember the conclusion statement should be of the following format: Since the p-value of # is more/less than the level of significance of #, the null hypothesis is/is not rejected; therefore, the data supports ( paraphrase the hypothesis supported).
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