# StatGraphics Assignment

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**YOU MUST HAVE **

**StatGraphics**

** IN ORDER TO DO THIS ASSIGNMENT **

**Project Assignment Details**

**Step 1: Assignment Data**

Download the data file __Project Assignment Data__. You’ll need to open statgraphics, then open by selecting File->Open->Open Data Source, choose “External Data File”, then browsing for your excel file.

**Step 2: Project Report**

As you work through the assignment, write your report using either the provided __Project Assignment 2 Template__ or create your own document from scratch.

**Page 1**

Make a cover page, including your name, the date, instructor’s name, and “Project #2: ANOVA test of multiple means”.

**Page 2**

Does response to the “Price” question vary by gender? [Use StatGraphics output. Cut & paste directly but only the requested information.]

*Hint: Compare—Multiple Samples—Multiple Sample Comparison—Data and Code Columns. Then use “Box and Whisker Plot” and use right mouse click—pane options for other modifications (like choosing vertical or horizontal plots, whichever fits your report better).*

- Use StatGraphics to generate side-by-side boxplots for Male and Female responses to the “Price” question.
- Generate an ANOVA report for the difference between these categories.
- Conduct (by hand or using statgraphics) a t test of the difference of these two means. How does this p-value compare to the p-value from your ANOVA table?
- Based on the boxplot; discuss the results; i.e., write a report (in your words, 25-50 words) --> Compare the table data. What does the “data tell you” about the difference between the genders on this question?

Reflection Question #1: on the previous project we used a chi-squared test to address this same data. What was the difference between these two approaches? Which approach is better, and why?

** Page 3**

Does the answer to the “Variety” question vary by zip code? [Use StatGraphics output. Cut & paste directly but only the requested information.

*Hint: Same as for page 2, and be sure “ANOVA Table” is checked as an option. For Reference: See statgraphics “how-to” videos*

- Use StatGraphics and generate and print an analysis of variance (ANOVA) table for the ”Variety” question with the three Zip Code levels “treatments”. Based on the table results, conduct a test of hypothesis about the equality of the true mean satisfaction with the variety of shows for all three treatment means in your words --> Use the p-value Method, α=0.05 and do the following, all within the context of the problem (i.e., in your words):
- Use StatGraphics and generate and print an analysis of variance (ANOVA) table for the ”Variety” question with the Age levels “treatments”. Based on the table results, conduct a test of hypothesis about the equality of the true mean satisfaction with variety across age levels: in your words --> Use the p-value method, α=0.10 and do the following, all within the context of the problem (i.e., in your words):

i.state the hypotheses;

ii.state the p-value; and

iii.state the conclusion (use the scenario information to state this, and use your rejection criteria)

i.state the hypotheses;

ii.state the p-value; and

iii.state the conclusion (use the scenario information to state this, and use your rejection criteria).

Reflection Question #2: Does it seem reasonable to you that we use two different levels of significance for these two questions? If so, why? If not, why not? In either case, when does it seem reasonable to you to use a different value than 0.05 for alpha?

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