Dale L. Zimmerman
Professor of Statistics
Department of Statistics and Actuarial Science
217 Schaeffer Hall
The University of Iowa
Iowa City, IA 52242
Phone: (319) 335-0818
Email: dale-zimmerman@uiowa.edu
Research Interests:
Spatial statistics, linear models, experimental design, multivariate
analysis, environmetrics, sports statistics
Reading assignments for STAT:3510:0BBB Biostatistics, Spring 2024, from Samuels et al.'s textbook:
January 17: Sections 1.1 and 1.3
January 19: Sections 2.1 and 2.2
January 22: Sections 2.3 and 2.6
January 24: Sections 2.4 and 2.7
January 26: Sections 2.8 and 2.9
Jamuary 29: Sections 3.1 and 3.2
January 31: Section 3.3
February 2: Section 3.5
February 5: Section 3.6
February 7: Sections 3.4 and 4.1
February 9: Section 4.2
February 12: Section 4.3
February 14: Sections 5.1 and 5.2
February 16: Sections 5.3 and 5.4
February 19: Catch-up
February 21: First Midterm Exam
%February 25: Sections 6.1-6.3
%February 28: Section 6.4
%March 2: Section 6.6-6.7
%March 4: Section 7.2
%March 7: Section 7.3
%March 9: Sections 7.5-7.6
%March 11: Section 7.10
%March 21: Sections 8.1-8.2
%March 23: Sections 8.3-8.4
%March 25: Section 8.5
%March 28: Sections 11.1-11.2
%March 30: Sections 11.3-11.4
%April 1: Section 11.5
%April 4: Catch-up
%April 6: Second Midterm Exam
%April 8: Sections 9.1-9.2
%April 11: Section 10.7
%April 13: Section 9.4
%April 15: Sections 2.5, 10.1-10.2
%April 18: Sections 10.3, 10.5
%April 20: Section 10.8
%April 22: Section 10.9
%April 25: Sections 12.1-12.2
%April 27: No reading
%April 29: No reading
%May 2: No reading
%May 4: No reading
%May 6: No reading
%
Homework assignments for STAT:3510:0BBB Biostatistics, Spring 2022, from Samuels et al.'s textbook:
Homework 1: Exercises 1.3.1bce, 1.3.2bc, 2.1.4, 2.2.4, 2.2.5, 2.3.3, 2.3.6, 2.3.7, 2.4.3 (also compute the range and IQR for part b), 2.4.5, 2.7.4; Due Friday, January 28
%Homework 2: Exercises 2.S.20, 2.S.22, 3.2.2, 3.2.3, 3.3.3, 3.3.4; Due Friday, February 4
%Homework 3: Exercises 3.4.2, 3.4.4, 3.5.1, 3.5.7, 3.5.8, 3.6.1, 3.6.4, 3.6.7; Due Friday, February 11
%Homework 4: Exercises 4.3.9, 4.3.11, 4.3.14, 4.3.15, 4.3.16, 5.2.5, 5.2.8, 5.2.9; Due Friday, February 18
%Homework 5: Exercises 6.2.2, 6.3.4, 6.3.6, 6.3.7, 6.4.1, 6.4.5, 6.6.9, 6.7.7, 6.7.11; Due Friday, March 4
%Homework 6: Exercises 7.2.5 (alternative hypothesis is two-sided), 7.2.9 (alternative hypothesis is two-sided),
%7.2.12 (alternative hypothesis is two-sided), 7.2.13 (alternative hypothesis is two-sided), 7.3.10, 7.5.8 (alternative %hypothesis is one-sided), 7.6.3; Due Friday, March 11
%Homework 7: Exercises 7.10.4, 7.10.7, 8.2.2, 8.2.7, 8.2.9, 8.4.5, 8.4.9; Due Friday, March 25
%Homework 8: Exercises 8.5.2, 8.5.5, 8.5.7, 11.2.2, 11.2.5, 11.4.1, 11.4.5, 11.4.6; Due Friday, April 1
%Homework 9: Exercises 9.2.6, 9.2.9, 9.2.10, 9.4.4, 9.4.12, 9.S.14, 10.7.1, 10.7.6; Due Friday, April 15
%Homework 10: Exercises 10.2.1, 10.2.6, 10.3.3, 10.3.8, 10.5.1, 10.5.4, 10.8.2, 10.8.4; Due Friday, April 22
%Homework 11: Exercises 10.9.9, 10.S.9, 12.2.4, 12.2.10; Due Friday, April 29
%Homework 12: Problem 1: For the data in Exercise 12.2.7 (i.e., X = laetisaric acid concentration, Y = fungus
%growth), (a) create the scatter plot; (b) obtain the least squares estimate of the intercept using the fact that the %least squares estimate of the slope is -0.712; (c) plot the least squares line on your scatterplot; (d) predict the %fungus growth when the laetisiric acid concentration is 15 (micrograms/ml); (e) obtain a 95% confidence interval for the %slope using the fact that the estimated slope's standard error is 0.03589; (f) obtain a 95% confidience interval for the %predicted fungus growth when the laetisiric acid concentration is 15 using the fact that this quantity's standard error %is 1.8325. Problem 2: For the data in Exercise 12.3.8 (i.e., X = length, Y = maximum jump), (a) create the scatter %plot; (b) obtain the least squares estimate of the intercept using the fact that the least squares estimate of the slope %is 0.3492; (c) plot the least squares line on your scatterplot; (d) predict the maximum jump when the length is 150 mm; %(e) perform a hypothesis test that the slope is equal to 0 at the 0.05 level of significance (against a two-sided %alternative hypothesis) using the fact that the estimated slope's standard error is 0.3965; (f) obtain a 95% confidence %interval for the predicted maximum jump when the length is 150 mm using the fact that this quantity's standard error is %18.96. Due Friday, May 6
Errata for Linear Model Theory: With Examples and Exercises, by Dale L. Zimmerman (2020), Springer.
Link to the pdf listing the errata
Errata for Probability and Statistical Inference, by R. V. Hogg, E. A. Tanis, and D. L. Zimmerman, 10th edition (2020): Pearson
1. Exercise 2.4-11: It should say "... and verify that it is positive if p < 0.5, zero if p = 0.5, and negative if p > 0.5."
2. Exercise 5.2-12: The known solution to this exercise requires some background in complex analysis, which is otherwise not a prerequisite for the book, so this exercise, though correct, really should not be included in the book. It will be removed in future editions.
3. Page 199: A better title for Section 5.5 would be "Distributions Associated with Sampling from Normal Distributions"
4. Exercise 6.4-21: The upper limit of support for x should be plus infinity, not theta.
5. Exercise 7.6-10: Symbols a, b, and c should be beta1-hat, beta2-hat, and beta3-hat, respectively.
6. Exercise 7.6-11: This exercise is correct, but out of place. Part (a) asks for the (sample) correlation coefficient, which is not defined until Section 9.6.
7. Exercise 7.7-6: This exercise is also correct but out of place as it involves calculation of the sample correlation coefficient, which is not defined until Section 9.6.
Dept. of Statistics and Actuarial Science