Resources

ACTS:3080 Mathematical Finance

Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022, Fall 2021

ACTS:4130 Quantitative Methods for Actuaries

Fall 2023, Fall 2022, Fall 2021

ACTS:4150 Fundamentals Short-Term Actuarial Math

Spring 2024, Spring 2023, Spring 2022

ACTS:4180 Life Contingencies I

Spring 2024, Spring 2023, Spring 2022

ACTS:4280 Life Contingencies II

Fall 2023, Fall 2022, Fall 2021

ACTS:4380 Mathematical Finance II

Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022, Fall 2021

ACTS:6200 Predictive Analytics

Spring 2024, Spring 2023, Spring 2022

ACTS:6480 Loss Distributions

Spring 2023, Spring 2022

ACTS:6580 Credibility and Survival Analysis

Spring 2023, Spring 2022

ACTS:7730 Adv Topics: Actuarial Sci/Financial Math

Spring 2024 

DATA:1015 Introduction to Data Science

Fall 2024, Fall 2023, Fall 2022

DATA:3120 (co-listed with STAT:3120) Probability and Statistics

Fall 2024, Fall 2023, Fall 2022

DATA:3200 (co-listed with STAT:3200) Applied Linear Regression

Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

DATA:4540 Statistical Learning

Fall 2024, Fall 2023, Fall 2022

DATA:4580 (co-listed with STAT:4580) Data Visualization and Data Technologies

Spring 2024, Spring 2023, Spring 2022

DATA:4600 Casual Inferences for Data Science

Spring 2024, Spring 2023, Spring 2022

DATA:4610 Data Acquisition and Management

Fall 2024, Fall 2023, Fall 2022

DATA:4750 Probabilistic Statistical Learning

Spring 2024, Spring 2023, Spring 2022

DATA:4880 Data Science Creative Component

Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

DATA:4890 Data Science Practicum

Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

DATA:5400 (co-listed with STAT:5400) Computing in Statistics

Fall 2024, Fall 2023, Fall 2022

DATA:5890 MS Data Science Practicum

Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

DATA:6200 (co-listed with ACTS:6200 and STAT:6200) Predictive Analytics

Spring 2024, Spring 2023, Spring 2022

DATA:6220 Consulting and Communication with Data

Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

DATA:7400 (co-listed with STAT:7400) Computer Intensive Statistics 

Spring 2024, Spring 2023, Spring 2022

STAT:1010 Statistics and Society

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:1015 (co-listed with DATA:1015) 

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:1020:AAA Elementary Statistics and Inference

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:1020:BBB Elementary Statistics and Inference

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:1030 Statistics for Business

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:2010 (co-listed with STAT:4200) Statistical Methods and Computing

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:2020 Probability & Stats for Engr & Phys Sci

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:3100  Introduction to Mathematical Statistics I

Fall 2024, Fall 2023, Fall 2022 

STAT:3101 Introduction to Mathematical Statistics I

Spring 2024, Spring 2023, Spring 2022

STAT:3120 Probability and Statistics 

Fall 2024, Fall 2023, Fall 2022 

STAT:3200 (co-listed with DATA:3200) Applied Linear Regression

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:3210 Experimental Design and Analysis

Spring 2024. Spring 2023, Spring 2022

STAT:3510:AAA  Biostatistics

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:3510:BBB Biostatistics

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:4100 Mathematical Statistics I

Fall 2024, Fall 2023, Fall 2022

STAT:4101 Mathematical Statistics II

Spring 2024. Spring 2023, Spring 2022

STAT:4520 Bayesian Statistics

Fall 2024, Fall 2023,  Fall 2022

STAT:4540 (co-exists with DATA:4540) Statistical Learning

Fall 2024, Fall 2023, Fall 2022

STAT:4560 (Co-listed with DATA:4560) Statistics for Risk Modeling I

Fall 2024, Fall 2023, Fall 2022

STAT:4561 (Co-listed with DATA:4561) Statistics for Risk Modeling II

Spring 2024. Spring 2023, Spring 2022

STAT:4580 (co-listed DATA:4580) Data Visualization and Data Technologies

Spring 2024. Spring 2023, Spring 2022

STAT:4740 Large Data Analysis

Fall 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:5100 Statistical Inference I

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:5101 Statistical Inference II

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:5200 Applied Statistics I

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:5201 Applied Statistics II

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:5400 (co-listed with DATA:5400) Computing in Statistics 

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:6300 Probability and Stochastic Processes I

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:6200 (co-listed with ACTS:6200 and DATA:6200) Predictive Analytics

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:6220 Statistical Consulting

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:6300 Probability and Stochastic Processes I 

Fall 2024, Fall 2023, Fall 2022

STAT:6301 Probability and Stochastic Processes II 

Spring 2024, Spring 2023, Spring 2022

STAT:6530 Environmental and Spatial Statistics

Fall 2024

STAT:6560 Applied Time Series Analysis

Spring 2024. Spring 2023, Spring 2022

STAT:7100 Advanced Inference I

Fall 2024,  Fall 2023, Fall 2022

STAT:7101 Advanced Inference II

Spring 2024, Spring 2023,  Spring 2022

STAT:7400 (co-exist with DATA:7400) Computer Intensive Statistics

Spring 2024, Spring 2023, Spring 2022

STAT:7520 Bayesian Analysis

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

STAT:7560 Time Series Analysis

Fall 2024, Spring 2024. Fall 2023, Spring 2023, Fall 2022, Spring 2022

 

Fall 2024 Courses and Textbooks

 

updated on June 14, 2024

Note: All textbooks are available at University Book Store. These are the books that have been selected, however changes may occur.

Actuarial Science — Fall 2024

ACTS:1001 INTRODUCTORY SEMINAR IN ACTUARIAL SCIENCE (1 s.h.) Instructor —  Barb Hogg
Required Text --  None

ACTS:3080  MATHEMATICS OF FINANCE I (3 s.h.)
Instructor —  N.D. Shyamalkumar
Required Text --  Vaaler, L.J.F., Harper, S.K., and Daniel, J.W. Mathematical Interest Theory (Third Edition), 2019, The Mathematical Association of America, ISBN: 978-1-4704-4393-1

ACTS:3110 ACTUARIAL EXAM P PREPARATION (1 s.h.)
Instructor —  Tianrun Wang
Required Text —  None required

ACTS:4130  QUANTITATIVE METHODS FOR ACTUARIES (3 s.h.)
Instructor — Elias Shiu
Required Text — Dickson, Hardy & Waters, Actuarial Mathematics for Life Contingent Risks, 3rd ed.

ACTS:4280  LIFE CONTINGENCIES II (3 s.h.)
Instructor — Elias Shiu
Required Text — Dickson, Hardy & Waters, Actuarial Mathematics for Life Contingent Risks, 3rd ed.

ACTS:4990 READINGS IN ACTUARIAL SCIENCE (arr.)
Independent Study

ACTS:6990 READINGS IN ACTUARIAL SCIENCE (arr.)
Independent Study

Data Science Courses — Fall 2024

DATA:3120  PROBABILITY AND STATISTICS (4 s.h.)
(cross-listed with STAT:3120)
Instructor — Aixin Tan
Recommended Text— Tanis & Hogg, A Brief Course in Mathematical Statistics, 2008, Prentice Hall.

DATA:3200  APPLIED LINEAR REGRESSION (3 s.h.)
(cross-listed with STAT:3200)
Instructor — Erning Li
Recommended Text —  None

DATA:4540  STATISTICAL LEARNING (1 s.h.)
(cross-listed with STAT:4540)
Instructor —Sanvesh Srivastava
Recommended Text —  TBD

DATA:4610  DATA ACQUISITION AND MANAGEMENT (3 s.h.)
Instructor — Ruitao Liu
Recommended Text —  none

DATA:4880  DATA SCIENCE CREATIVE COMPONENT (1 s.h.)
Instructor —Erning Li
Recommended Text —  none

DATA:4890  DATA SCIENCE PRACTICUM (2 s.h.)
Instructor —Sanvesh Srivastava
Recommended Text —  none

DATA:5400  COMPUTING IN STATISTICS (3 s.h.)
(cross-listed with STAT:5400)
Instructor —Boxiang Wang
Recommended Text —  none

DATA:5890  M.S. DATA SCIENCE PRACTICUM (2 s.h.)
Instructor —Sanvesh Srivastava
Recommended Text —  none

Statistics Courses — Fall 2024

STAT:1010 STATISTICS AND SOCIETY (3 s.h.)
Lecture AAA (sections A01-A04)
Instructor —  Alex Liebrecht
Required Text — Statistical Reasoning for Everyday Life by Bennett, Briggs, and Triola.  5th ed. Pearson.

STAT:1020  ELEMENTARY STATISTICS AND INFERENCE (3 s.h.)

Lecture AAA (sections A11-A14)
Instructor — Robert Ankenmann
Required Text —Intro Stats, 6th Edition (2022) by DeVeaux, Velleman, and Bock, Pearson Publishing.  ICON Direct. 

Lecture BBB (sections B21-B24)
Instructor —  Robert Ankenmann
Required Text — Intro Stats, 6th Edition (2022) by DeVeaux, Velleman, and Bock, Pearson Publishing.  ICON Direct. 

Lecture CCC (sections C31-C40)
Instructor — Alex Liebrecht
Required Text — Intro Stats, 6th Edition (2022) by DeVeaux, Velleman, and Bock, Pearson Publishing.  ICON Direct.

STAT:1030  STATISTICS FOR BUSINESS (4 s.h.)
Lecture AAA (sections A01-A17)
Instructor —   Joseph Lang
Required Text — None required.

STAT:2010  STATISTICAL METHODS AND COMPUTING (3 s.h.)
Lecture AAA (sections A11-A14)
Instructor —  Erning Li
Required Text — Basic Practice of Statistics, 9th ed. Moore, Notz, Fligner. ICON-Direct. 

STAT:2020  PROBABILITY AND STATISTICS FOR THE ENGINEERING AND PHYSICAL SCIENCES (3 s.h.)
Lecture AAA (sections A11- A18)
Instructor — Matt Bognar
Required Text — Probability & Statistics for Engineers & Scientists, Wapole, Myers, Myers, and Ye book (9th ed),  ICON-Direct

STAT:3100:0001 INTRODUCTION TO MATHEMATICAL STATISTICS II (3 s.h.)
Instructor — Nathan Wikle
Required Text —  Probability and Statistical Inference (10th Edition), Hogg, Tanis and Zimmerman, Pearson.

STAT:3120  PROBABILITY AND STATISTICS (4 s.h.)
(cross-listed with DATA:3120)
Instructor — Aixin Tan
Recommended Text— Tanis & Hogg, A Brief Course in Mathematical Statistics, 2008, Prentice Hall.

STAT:3200  APPLIED LINEAR REGRESSION (3 s.h.)
(cross-listed with DATA:3200)
Instructor — Erning Li
Required Text - None

STAT:3510  BIOSTATISTICS (3 s.h.) 
Lecture AAA (A11-A18)
Instructor —  Matt Bognar
Required Text — Statistics for the Life Sciences, 5th edition, ISBN: 9780321989581, ICON Direct

STAT:4100   MATHEMATICAL STATISTICS I (3 s.h.)
Instructor — Osnat Stramer
Recommended Text — Casella & Berger, Statistical Inference, 2nd. ed.

STAT:4200  STATISTICAL METHODS AND COMPUTING (3 s.h.)
Lecture AAA (sections A11-A14)
Instructor —  Erning Li
Required Text — Basic Practice of Statistics, 9th ed. Moore, Notz, Fligner. ICON-Direct. 

STAT:4540 STATISTICAL LEARNING (3 s.h.)
(cross-listed with DATA:4540)
Instructor — Sanvesh Srivastava
Recommended Text — TBD

STAT:4560 STATISTICS FOR RISK MODELING (3 s.h.)
Instructor — N.D. Shyamalkumar Required Text: Regression Modeling with Actuarial and Financial Applications, Edward W. Frees, 2010, New York: Cambridge. ISBN: 978-0521135962.

STAT:5090   ALPHA Seminar (1 s.h.)
Instructor — Boxiang Wang
Recommended Text —  none

STAT:5100  STATISTICAL INFERENCES I (3 s.h.)
(cross-listed with STAT:4100) Instructor — Osnat Stramer
Recommended Text — Casella & Berger, Statistical Inference, 2nd. ed.

STAT:5200  APPLIED STATISTICS I (3 s.h.)
Instructor — Andrew Thomas
Recommended: Introduction to Regression Modeling, Abraham and Ledolter 

STAT:5400   COMPUTING IN STATISTICS (3 s.h.)
(cross-listed with DATA:5400)
Instructor — Boxiang Wang
Required Text —  None required

STAT:6300   PROBABILITY AND STOCHASTIC PROCESSES I (3 s.h.)
Instructor — Osnat Stramer
Required Text —none

STAT:6530 ENVIRONMENTAL AND SPATIAL STATISTICS 
Instructor- Dale Zimmerman 
Required Text - Spatial Linear Models for Environmental Data, D. Zimmerman

STAT:6990 READINGS IN STATISTICS (arr.)
Independent Study.

STAT:7190 SEMINAR: MATHEMATICAL STATISTICS  (1 s.h.)
Instructor - Dale Zimmerman

Required text- none

STAT:7200  LINEAR MODELS (4 s.h.)
Instructor – Dale Zimmerman
Required Text — Linear Model Theory with Examples and Exercises, Dale Zimmerman. Springer Publishing.

STAT:7290 SEMINAR: APPLIED STATISTICS  (1 s.h.)
pending
 

STAT:7390 SEMINAR: PROBABILITY  (1 s.h.)
pending

STAT:7990 READING RESEARCH (arr.)
Independent Study

-----------------------------------

  • All instructors will be asked to order textbooks each semester before the start of Early Registration for the following semester so that UI complies with the HEO Act. The law does allow for some exceptions. If placing the textbooks online is “impractical,” the tag of “To be determined” may be added to the course schedule instead. However, the law also indicates that institutions (rather than each individual) defines more specifically what is considered “impractical” and when “To be determined” may be used.  At the University of Iowa, “To be determined” may be used in these circumstances:
    • If an instructor has not yet been hired
    • If the instructor has not yet been assigned to a course
    • If the course is new and still under development
    • If the textbook is new and still under development

 

Information technology resources

Email information: Office 365 account

Eligibility for your UI email account will end two years after graduation. If you continue to take courses, your account closes two years after completion of your last class.  If you are employed at the university, your account will remain open.Several notifications will be sent before the account closes to provide time to create a new account elsewhere and move messages you want to keep.

If you no longer wish to use your Office 365 account after graduation, you should contact the ITS Help Desk to have it closed. Prior to having the account closed, you will want to save all of your files from your OneDrive cloud storage and forward on any email you wish to keep.

If you have questions, please call the ITS Help Desk at 319-384-4357 or e-mail its-helpdesk@uiowa.edu.

How to move emails from your UI account to an alternate email account: Here is a link explaining how you can move/copy your emails from your Office 365 account to an alternative email account: http://its.uiowa.edu/support/article/102567.

Information Technology Services (ITS) 

ITS provides a wide variety of computing services to students, faculty, and staff.    

Instructional Technology Centers (ITCs) provide students with campus-wide access to the University's academic computing resources, and to encourage departments to integrate computing into their academic programs. ITCs are located in 26 locations on campus, comprising a network of over 1000 workstations available for student use. Wherever you are on the University of Iowa campus, there is an ITC nearby to meet your technology needs!

The Statistics ITC, located in 41 Schaeffer Hall, has 28 Windows desktop computers, which are available to students, faculty and staff who have a Hawk ID.

CLAS Linux Group

In addition, we have computer support from the College of Liberal Arts with the CLAS Linux Group. They provide a stable, secure, productive computer environment that allows the College of Liberal Arts & Sciences to achieve its educational, research and administrative needs. This includes the basic network infrastructure and computing environment for the state of the art Linux workstations used in labs, faculty offices or research projects. Supported services include managed Linux loads, file services (including backup), college and personal web hosting, public printers, DNS, DHCP, and a hot disaster recovery site for core services. 

The goal of the team is to improve the quality of education and research through out the College by working together with faculty and staff to maximize the availability of core network services and provide exceptional Linux & research support. 

The services they support can be found on the CLAS Linux Group site.

The UNIX (Linux) Lab, located in 346 Schaeffer Hall and supported by the CLAS Linux Group, provides an up-to-date learning experience for departmental majors and students who have UNIX accounts. In the lab, students can use powerful graphic-oriented computational software on UNIX workstations to explore statistical concepts. Any CLAS user can create a Linux account that will remain active until the user leaves the University. 

High Performance Computing information