Many of these require computer work. Some require more thought than typical quizzes. Each will be assigned one day to be turned in the following day. You are encouraged to use this page to get a head start on working them and asking questions about them.

Project A (3 pts) : (Can be done after Chapter 1, section 1)

Example: I might want to measure the lengths of cats. The cases (also called individuals) are cats, and the variable is "length", in inches, measured to the nearest inch. Some questions which occur are (1) Should I include the tail? and (2) If I include the tail, do I measure to the tip of the fur or just to the tip of the tail without the fur? Other variables which might be interesting are "weight" and their "eye color". Observations on the length of a cat might be 15 inches, 18 inches, 12 inches, and 13 inches.

Now, you do one. Think of some variables which you might be interested in analyzing sometime.

5. For that variable, give four observations that would be reasonable to see.

Project B: (2 pts) Special questions about analyzing the data in Chapter 7, problems 74, 75, and 76. (Can be done anytime after Chapter 2, section 1.)

1. Make an appropriate graph to illustrate the distribution of city pollution levels. Describe the distribution: shape, center, and variation.
2. Make an appropriate graph to illustrate how, for each day, the city pollution level and the rural pollution level compare. Summarize this in words and numerical estimates. (There is more than one good way to do this. There are also incorrect ways to do this. Choose a graphing procedure that answers the question.)

Project C: (4 pts) More special questions about analyzing the data in Chapter 7, problems 74, 75, and 76 (Can be done anytime after Chapter 2, section 3.)

1. Make a scatterplot and find the regression line to predict city pollution from rural pollution. Interpret each of the coefficients in words.
2. Make a residual plot of the residuals versus the x-variable and interpret it.
3. Use the "fit" subcommand or menu choice to get the computer to predict the city pollution on a day when the rural pollution is 78. Cut out and hand in the appropriate part of the computer printout.
4. Write a sentence describing how well one can predict city pollution on a day from rural pollution on that same day. Include a reference to any useful statistics.

Project D: (3 pts) Chapter 2, problem 38. In addition to the questions in the problem, also look at the MINITAB output in the Session Window for information about influential points. This is a good problem to practice because you know that the dataset has at least one influential point, so you can see that in the output. What does MINITAB tell you about whether Child 19 is influential? What can you see about whether Child 19 is influential based on the calculations and graphs you're being asked to do in the problem? Does what you have observed agree with what MINITAB tells you about Child 19? Print the relevant part of the Session Window and include that output along with your discussion.

Project E: (6 pts) (Can be done anytime after Chapter 3, section 2) Plan a study.

1. Formulate the question. Think of a question of interest to you for which you (you, as a student and an individual) could collect some data.
   Examples:

1. What percentage of cars don't completely stop at the stop sign at the north corner of Waterston and Hartford?
2. In a blind taste test, do people prefer Classic Coke to Pepsi?
3. How accurately could we predict hat size from forearm length?

1. Identify relevant variable(s).
   Explain what the variable(s) is and how you expect to measure it. Discuss any definitions needed. (Remember the example about the length of a cat -- does that include the tail or not?)
2. How would you collect useful data?
   Is this a question for which you just go collect data or do you have to set up an experiment? (Example b above requires you to set up an experiment.) Explain how you could get a reasonable sample or set up a reasonable experiment. Describe the population in which you are interested and explain how this method of collecting data should get representative data from this population.

Project F: (3 pts) Chapter 2, problem 96. Similar to Chapter 2, problem 15, except now you must use the LET command on the computer to find the logarithms. This problem illustrates a common technique used in regression analysis, in which transformations of one or both variables are used in order to find a better straight-line relationship. We will not do very much of that in this class, but a second statistics course would do this in much more depth.

Project G: (6 pts) Chapter 2, problem 98. Do this as if it were a report to your supervisor at work, who needs to understand this data. Write about a one-page summary of the results for the problem, answering all the questions asked. Cut pieces from your computer output, label them appropriately, and put them into your report in appropriate places. Make sure that your narrative has appropriate explanations of the computer output shown. (3 points for the analysis, 3 points for the presentation)

Project H: (3 pts) Chapter 11, number 24. (Can be done anytime after Chapter 2, section 3) Answer all the questions in the problem except for the confidence interval part of c. For part c, just use the computer to make the prediction and cut out that part of the computer output to include in your answer. Include the part of the output that has the confidence interval, even though you haven't yet learned to interpret it.

Project I: (3 pts) Chapter 11, number 25. (Can be done anytime after Chapter 2, section 3). Answer all the questions in the problem except for the confidence interval part of e. For part 3, just use the computer to make the prediction and cut out that part of the computer output to include in your answer. Include the part of the output that has the confidence interval, even though you haven't learned to interpret it.

Project J: (6 pts) Chapter 7, problems 74, 75, and 76. Do this as if it were a report to your supervisor at work, who has been asked to provide a statistical analysis of the data for a client of your firm. Write a one- or two-paragraph summary of the results for each problem, mentioning your answers to all the questions asked in the problem, the techniques you used to answer the question, and how you checked to make sure the techniques were appropriate. Show some of your computer output as supporting material for your summaries. (3 points for the analysis, 3 points for the presentation)