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:


Reading assignments for STAT:3510:0BBB Biostatistics, Spring 2022, from Samuels et al.'s textbook:

January 19: Sections 1.1 and 1.3
January 21: Sections 2.1 and 2.2
January 24: Sections 2.3 and 2.6
January 26: Sections 2.4 and 2.7
January 28: Sections 2.8 and 2.9
Jamuary 31: Sections 3.1 and 3.2
February 2: Section 3.3
February 4: Section 3.5
February 7: Section 3.6
February 9: Sections 3.4 and 4.1
February 11: Section 4.2
February 14: Section 4.3
February 16: Sections 5.1 and 5.2
February 18: Sections 5.3 and 5.4
February 21: Catch-up
February 23: 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 1.3.1bcd, 1.3.2bc, 2.1.4, 2.2.2, 2.2.3, 2.3.2, 2.3.3, 2.3.6, 2.4.3, 2.6.3 (also compute the range and IQR for part b), 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

Reading assignments for STAT:5201 Applied Statistics II, Spring 2022, from Oehlert's textbook:

January 19: Chapter 1, also read the papers by Schindler and by Mowafy and Cassens in ICON Files
January 21: Sections 2.1-2.4
January 24: Sections 2.5, 3.1-3.2
January 26: Sections 3.3-3.6
January 28: Sections 3.7-3.10
Jamuary 31: Sections 3.11, 4.1-4.2
February 2: Sections 4.3-4.5
February 4: Sections 5.1-5.2
February 7: Sections 5.3-5.4.3
February 9: Sections 5.4.4-5.4.9
February 11: Sections 5.5-5.9
February 14: Sections 6.1-6.3
February 16: Section 6.4
February 18: Sections 6.5-6.7, 7.1-7.2
February 21: Sections 7.3-7.4 (but skip stuff on power curves)
February 23: Sections 7.5-7.7, Supplement called "Optimal Allocation of EU's to Treatments"
February 25: Sections 8.1-8.3
February 28: Sections 8.4-8.6
March 2: Exam 1 (Coverage: Chapters 1-7)
March 4: Sections 8.7-8.9
March 7: Sections 8.10-8.11
March 9: Sections 9.1, 9.2.1-9.2.2
March 11: Sections 9.2.3-9.3
March 21: Sections 10.1-10.2
March 23: Sections 10.3-10.4.1
March 25: Sections 10.4.2-10.5
March 28: Sections 11.1-11.3
March 30: Sections 11.4-11.5
April 1: Sections 11.7-11.8
April 4: Sections 12.1-12.3
April 6: Section 12.4-12.5
April 8: Section 12.6
April 11: Exam 2 (Coverage: Chapters 8-11)
April 13: Section 12.7-12.8
April 15: Sections 13.1-13.2
April 18: Sections 13.3.1-13.3.4 plus supplement called "blocking-demonstration.pdf" in ICON course directory
April 20: Sections 13.4-13.5
April 22: Sections 14.0-14.1.1
April 25: Section 14.2
April 27: Sections 15.0-15.1.2
April 29: Sections 15.1.3-15.1.4
May 2: Sections 16.1-16.2
May 4: Sections 16.3-16.4
May 6:

Homework assignments for STAT:5201 Applied Statistics II, Spring 2022, from Oehlert's textbook:

Homework 1: Exercises 2.1, 2.5, Problem 2.2; due January 26
Homework 2: Exercises 3.2 and 3.4, Problems 3.2 and 3.3; due February 2
Homework 3: Exercise 4.1, Problems 4.1 and 4.2, Question 4.1; due February 9
Homework 4: Exercise 5.1 (obtain Bonferroni, Scheffe, and Tukey-based simultaneous confidence intervals), Exercise 5.3 (in addition to the requested procedure that controls the SFER at epsilon=0.05, also perform procedures that control the FDR and EER at epsilon=0.05), Exercise 5.5 (use only the two-sided Dunnett procedure at epsilon=0.05), Problem 5.1 (use not only Tukey's HSD procedure but also the REGWR and SNK procedures at epsilon=0.05); due February 16
Homework 5: Exercises 6.1, 6.3 (be sure to check assumptions in addition to making the stated determinations), 6.5, 7.3, 7.5, Problem 7.1; due February 25
Homework 6: Exercise 8.1, Problems 8.1, 8.5, 8.6, 8.7; due March 11
Homework 7: Problems 9.1, 9.4, 9.5, Question 9.3. For the three problems, construct interaction plots and check for one-cell interaction, and, if appropriate, do Tukey's 1-df-for-nonadditivity test. Also for Problem 9.5, test for the significance of polynomial cisplatin dosage contrasts/terms, if warranted, after transforming the dosages to 0,1,...,5; due March 23
Homework 8: Exercises 10.2 and 10.4, Problems 10.2, 10.6, 10.8; due March 30
Homework 9: Exercises 11.3 (instead of a CI, obtain point estimates of variance components and determine whether there is evidence for type to type variability), 11.4, Problems 11.2 and 11.3 (only the point estimates, no CI); due April 6
Homework 10: Exercises 12.2 and 12.4, Problems 12.3, 12.4, 12.7; due April 18
Homework 11: Exercises 13.3 (don't transform), 13.4, 14.2, 14.4 (don't transform); Problems 13.3, 13.8 (don't transform), 13.11 (transform); due April 27, but can submit for full credit on April 29
Homework 12: Exercises 15.2, 15.3, Problems 15.1abc, 15.4, 16.2, 16.3; due 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. Page 199: A better title for Section 5.5 would be "Distributions Associated with Sampling from Normal Distributions" 3. Exercise 6.4-21: The upper limit of support for x should be plus infinity, not theta.
4. Exercise 7.6-10: Symbols a, b, and c should be beta1-hat, beta2-hat, and beta3-hat, respectively.
5. 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.
6. 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.

STAT:6530 Spatial and Environmental Statistics
STAT:7290 Sports Statistics
R functions for antedependence models (under construction)
Data for antedependence models

 
 
 
 
 
 
 
 
 
 
 

Dept. of Statistics and Actuarial Science