Online STAT Course Descriptions


We also offer a set of graduate level courses that are focused primarily on statistical applications, without as much emphasis on theoretical development. These courses have a separate prefix - STAA. For descriptions of the STAA courses, click here.

The courses below are offered based on availability and student interest. Courses are offered with video lectures available by streamed video. If you would like to obtain a generic version of a course syllabus, please contact Dr. Anderson. The schedule of online STAT course offerings can be found here.

Notes:

  1. We enforce our prerequisites! If you cannot show that you have taken the prerequisites for a course, you may be dropped from the class roster. Please make sure that you have the indicated prerequisites before registering!
  2. All STAT courses run the full semester (16 weeks), unless otherwise indicated.
  3. Courses are run asynchronously (no scheduled online class 'meetings', but on a fixed schedule - not self-paced.)
  4. Classes with proctored exams generally give a 4-6 day window (including a weekend) in which students must complete exams.


 


STAT 301 - Introduction to Statistical Methods 03 credits

Techniques in statistical inference; confidence intervals, hypothesis tests, correlation and regression, analysis of variance, chi-square tests.

Prerequisite: MATH 117 or MATH 118 or MATH 124 or MATH 125 or MATH 126 or MATH 141 or MATH 155 or MATH 160 or written consent of instructor.

Text: Cartoon Introduction to Statistics 1st Ed. ISBN: 978080903359 - Optional

- OpenIntro Statistics 3rd edition is recommended, it can be downloaded for free at https://www.openintro.org/stat/textbook.php

Computer Software: 

Proctor: This course requires an approved proctor for exams.

Credit allowed for only one course: STAT 301, STAT 307/ERHS 307, STAT 315, STAT 311.

To register for this course, click here.

 

STAT 500 - Statistical Computer Packages 01 credits

Comparison, evaluation, and use of computer packages for univariate and multivariate statistical analyses.

Prerequisite: (STAT 340; STAT 350) or admission to the Master of Applied Statistics program or written consent of instructor.

Text: No textbook required.

Computer Software: R (available as free download) and SAS (available by purchasing a discounted SAS license through CSU or as a free online tool using SAS OnDemand). Students will be given instructions on obtaining computer software when the course begins and are encouraged to wait for those instructions before trying to obtain the software.

Proctor: This course does not require a proctor.

To register for this course, click here.

 

STAT 511A - Design & Data Analysis for Researchers, I: R Software 04 credits

Statistical methods for experimenters and researchers emphasizing design and analysis of experiments.

Additional course details: Course involves weekly homework assignments (with analysis performed using R), 2 proctored mid-term exams, a proctored final exam, and a total of 54 hours of video lectures.

Prerequisite: STAT 301 or STAT 307 or EH/EHCC 307 or STAT 315 (ST309) or STAT 311 or written consent of instructor.

Text: An Introduction to Statistical Methods and Data Analysis 6th ed., Ott & Longnecker.

Proctor: This course requires an approved proctor for exams.

Computer Software: R. No prior knowledge of R is assumed, although familiarity with Microsoft Windows and an internet browser (Firefox, Netscape or Internet Explorer) is expected.

Notes:

  1. This course has a heavy computing component. Students are expected to use R statistical software to perform computations for completing homework assignments. An introduction to R is provided as part of the course.
  2. This course serves as an elective for the Certificate in Data Analysis. Does not count toward requirements for the MS or MAS degrees in Statistics.
  3. This course is approved by the Society of Actuaries for the regression component of the Validation by Educational Experience (VEE).
  4. Students must have access to fax or scanner.

To register for this course, click here.



STAT 512 - Design & Data Analysis for Researchers II 04 credits

Model building and decision making; communication of statistical information.

Additional course details: The major topics covered are: (1) Multiple regression, (2) Fixed-effect factorial designs, and (3) Random and mixed-effect factorial designs. The material in the text is supplemented by additional topics and computer package instruction.

Prerequisite: STAT 511.

Text: An Introduction to Statistical Methods and Data Analysis, 6th ed., Ott & Longnecker.

Proctor: This course requires an approved proctor for exams.

Computer Software: SAS. For information regarding SAS, click here. No prior knowledge of SAS is assumed, although familiarity with Microsoft Windows and an internet browser (Firefox, Netscape or Internet Explorer) is expected.

Notes:

  1. This course has a heavy computing component. Students are expected to use SAS statistical software to perform computations for completing homework assignments. An introduction to SAS is provided as part of the course.
  2. This course serves as an elective for the Certificate in Data Analysis. Does not count toward requirements for the MS or MAS degrees in Statistics.
  3. This course is approved by the Society of Actuaries for the regression component of the Validation by Educational Experience (VEE).
  4. Students must have access to fax or scanner.

To register for this course, click here.

 


STAT 699 - Thesis Variable Credit

Student must have an advisor for their project or thesis before registering for this class. Ideally you should start this before your final semester.

This course fulfills a Group I requirement for the MS degree.

To register for this course, click here.

 

Contact the Statistics Department Online Learning Program Office:

Phone: (970) 491-5268
Fax: (970) 491-1084
Email: stats_ddp@mail.colostate.edu
Follow us on Twitter: @CSUSTATDistance

Mailing Address:
Online Learning Office
Statistics Department
Colorado State University
1877 Campus Delivery
Fort Collins, CO 80523-1877

Jana Anderson, Associate Professor
Advisor for MAS and Certificate Programs
Department
of Statistics