Question 1. A large scale marketing survey was conducted. Some of the variables collected were:

gender             the person's gender (female or male)
income.group   the person's annual income (<$20,000, $20-30,000, $30-40,000 or >$40,000)
annual.income  the person's annual income (in thousands of dollars)
age                   the age of the person
leisure               the number of hours leisure time per week, on average
marital.status   the person's marital status (single, married, divorced or de facto)
work                 the average number of hours worked per week
home                whether the person owned their own home (yes or no)

• For these questions we want you to do the full analysis and write a Report. Your answers should be in three parts.

First: Technical Notes on the analysis. See the Case Studies.

Second: Executive Summary of the main findings of the analysis. See the Case Studies.

Third: R output. Include all necessary R output used in answering all of these questions as an appendix at the end of your assignment. These are for the markers to refer to if you make any mistakes in your analysis, so they can consider giving partial credit. There are no marks allocated for the R output, all the marks are for the Technical Notes and Executive Summary.

Please try to keep this section as small as possible - use the layout20x() command to save space for multiple plots. Remember: When you cut and paste R output into a word processor, you should use a "fixed" font such as Courier.

Question 2.

A biologist was interested in determining whether there were any differences in average petal length for 3 varieties of iris. The resulting data in the text file "iris", which contains the variables:

petal the length of the petal
variety the type of iris:
setosa = Iris setosa
versic = Iris versicolor
virg = Iris virginica

Question 3.

HDL cholesterol is known as the "good cholesterol'" as it is associated with lower risks of problems like heart disease. The following data were collected on random samples of people working in New Zealand companies. People were divided into groups based on the amount of exercise and strenuous activities they reported and their gender. The resulting data is stored in the text file "hdl", which contains the variables:

hdl               the level of hdl cholesterol in the subject's blood
gender        the gender of the subject:
                   female or male
exercise     the amount of exercise:
                  lowest, medium or most

Scenario 1:

What is the average age for each income group, and do the average ages differ for different income groups?

Scenario 2:

What effect do gender and marital status have on annual income?

Scenario 3:

Is there a difference in the average annual income between men and women?

Scenario 4:

Is the distribution of income (by group) the same for men and women?

Scenario 5:

Is an individual's annual income able to be predicted in terms of their age?

For each of the five scenarios:

(i) Identify ALL variables of interest. Classify each of them as either qualitative or quantitative.

(ii) Is there a response variable, or are we interested in analysing counts? If there is a response variable, what is it?

(iii) State which one of the following types of analysis would be most appropriate:

A: One-way Table of Counts
B: Two-way Table of Counts
C: One Sample t-test
D: Paired Data t-test
E: Two Sample t-test
F: Regression
G: One-way ANOVA
H: Two-way ANOVA

Question 4. A large company runs a regular training course for new managers in entry-level positions. The course tries to teach the basic engineering skills needed to understand the company's products to managers with no technical background. After complaints about the course, an experiment using 20 new managers is run to test two different class formats (traditional lectures or group discussions) and two different types of instructional material (standard textbook or purpose-written workbook). Five of the 20 managers were assigned at random to the four experimental groups and each was given a comprehesive test on the material at the end of the course. The results are stored in the text file "testscore", which contains the variables:

score            the manager's score on the test
lecture          the teaching method used:
                     lect = lecture
                    disc = discussion
book             the type of book used:
                    text = textbook
                    workbook = purpose-written workbook