Exercise 9.2 Consider the data set DaytonSurvey (described in Example 2.6), giving results of a survey of use of alcohol (A), cigarettes (C), and marijuana (M) among high school seniors. For this exercise, ignore the variables sex and race, by working with the marginal table Dayton.ACM, a 2 × 2 × 2 table in frequency data frame form.

Exercise 8.4 Refer to Homework #5, second question for a description of the Vietnam data set in vcdExtra. The goal here is to fit models for the polytomous response variable in relation to year and sex.

Exercise 7.5 The data set Caesar in vcdExtra gives a 3 × 2 frequency table classifying 251 women who gave birth by Caesarian section by Infection (three levels: none, Type 1, Type2) and Risk, whether Antibiotics were used, and whether the Caesarian section was Planned or not. Infection is a natural response variable. In this exercise, consider only the binary outcome of infection vs. no infection.

The data file Weeklylab9data.xlsx contains workers performance (a percentage based on several factors such as output, quality of output, follow safety procedures, team work, etc.) in a production facility. Production was measured under two conditions for each worker (before and after lunch) and each worker had one kind of production task out of two (weld or bolt). Analyze the data using a repeated measures ANOVA and then as a mixed effects regression model to see if there is any difference in performance before or after lunch, or for different kinds of tasks.

The data file Weeklylab7data.xlsx contains mock data on relationship satisfaction (measured on a scale from 0 to 100) for 200 individuals. Other variables include Sex (0 male, 1 female), age (continuous), shared house work (0 no, 1 yes), nights spent together on average per week (0 to 7), and financial security measured on a scale from 0 (heavily in debt) to 10 (very secure). Your goal is to build a model that predicts satisfaction using these variables. Summarize your findings and include and a graph

The data file Weeklylab8data.xlsx contains participant attractiveness ratings of three versions of a commercial product. Each participant was assigned to a focus group (4-6 participants were in each focus group) and everyone in the focus group rated the same version of the product on a scale from 0 to 100 (larger numbers more support for the product). Focus groups were constructed in several different cities across the NE. Standard demographic questions were included so that they could be used to vary out their potential effects. Analyze the data, being sure to take into account the nesting structure, and summarize the results.