Chapter 13: Inference for Tables
§ chi-square test for goodness of fit
§ segmented bar chart
§ chi-square statistic
§ expected count
§ observed count
§ degrees of freedom
§ chi-square distribution
§ components of chi-square
§ cell counts
§ r x c table
§ sum ( )
§ c2cdf (leftbound, rightbound, df)
§ c2pdf (X, df)
§ Shade c2 (leftbound, rightbound, df)
13.1 Test for Goodness of Fit (pp.728-744)
1. What information does a segmented bar chart show?
2. Explain how to construct a segmented bar chart. Draw a sketch.
3. What is the chi-square statistic?
4. What is the difference between the notation X2 and c2?
5. How many degrees of freedom does the chi-square distribution have?
6. As the chi-square statistic increases, what happens to the P-value?
7. What is the domain of a chi-square distribution?
8. What is the shape of a chi-square distribution? What happens to the shape as the degrees of freedom increases?
9. State the null and alternative hypotheses for the goodness of fit test.
10. What conditions must be met in order to use the goodness of fit test?
11. What is meant by a component of chi-square?
12. What does the largest component of chi-square signify?
13.2 Inference for Two-Way Tables (pp.744-775)
1. Why is it necessary to perform follow-up analysis to a chi-square test?
2. What information is contained in a two-way table for a chi-square test?
3. State the null and alternative hypotheses for comparing more than two proportions.
4. How do you calculate the expected count in any cell of a two-way table when the null hypothesis is true?
5. How many degrees of freedom does a chi-square test for a two-way table with r rows and c columns have?
6. If you have an entire population, or a single SRS, with each individual classified according to both of two categorical variables, what is the null hypothesis for a chi-square test?