Group members:

Paper Airplane one-way ANOVA class participation assignment

Monday 3/7/11

Worth 30 points

In the second week of classes, we randomly assigned ourselves to 4 different airplane design groups. We then flew the planes and recorded the distance flown. That data has been entered into SPSS, and the output is pasted at the end of this document. Use the appropriate output to answer one-way ANOVA questions. You will not submit this handout, but this handout will help you answer questions on the Blackboard assessment. The Blackboard assessment for this activity is due at 11:59 pm Friday 3/11/11.

  1. Why is this a one-way ANOVA situation?
  1. Is it appropriate to pool the variances for the data from your class? Explain your answer. What happens if the answer is “no”? Why does this check matter?
  1. Comment on what you see on the means plot. Which design flew the farthest? Which the shortest? Are all the designs very different, or are some fairly similar in distances?
  1. Comment on what you see on the side-by-side boxplots for the different sections. Is there a lot of overlap with the boxes? Where do you expect to see significant differences with ANOVA later? Where do you not expect to see significant differences?
  1. Regardless of your answer to #2, state the hypotheses for the one-way ANOVA test for this situation.
  1. Using the SPSS output for your class, state the F test statistic and the P-value.
  1. State your conclusion to the one-way ANOVA test in #5 in terms of the airplane story. Use α = 0.05.
  1. What is the R2 value for the data from your class for one-way ANOVA? What does R2 mean? Show how you found this.
  1. What is the estimate for the pooled standard deviation for this one-way ANOVA test? Show how you found this.
  1. How do you know when you need to look at the Bonferroni multiple comparisons test? What will Bonferroni tell you?
  1. For your class data, do we need to look at the Bonferroni multiple comparisons test? Why or why not? Write the hypotheses that would be used in the Bonferroni test (with labels).
  1. For your class data, if you answered “yes” to #11, state the overall conclusions to the Bonferroni multiple comparisons test in terms of the story.
  1. For each of the following aspects of the output, put an X through any features that are related to the sample data only, and circle any features that give you information about the whole population:

Side-by-side boxplot Means plot Summary statistics

ANOVA test Bonferroni multiple comparisons

Results from the 12:30 Spring 2011 class (DISTANCE, in)

Key: 1 = Nick’s, 2 = Floating, 3 = Origami, 4 = Worst Ever

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