College of Natural Sciences

Master of Applied Sciences

Current Students

Course Schedule

Subterm 1 (August)Subterm 2 (1st half Fall)Subterm 3 (2nd half Fall)Subterm 4 (1st half Spring)Subterm 5 (2nd half Spring)Subterm 6 (May/June)
MSSA-Mathematical Tools for Statistics

STAA551-Regression Models and Applications

STAA552-Generalized Regression Models

STAA553-Experimental Design

STAA554-Mixed Models

STAA556-Statistical Consulting

CSSA-Computing Tools for Statistics

STAA561-Probability with Applications

STAA562-Mathematical Statistics with Applications

STAA565- Quantitative Reasoning

STAA568-Topics in Industrial and Organizational Statistics

 
 

STAA566-Computational and Graphical Statistics

STAA567-Methods in Simulation and Computation

STAA571-Survey Statistics

 

STAA574-Methods in Multivariate Analysis

 
 

STAA572-Non-parametric Methods

STAA573-Analysis of Time Series

STAA575-Applied Bayesian Statistics

STAA577-Statistical Learning and Data Mining

 

Registration and Drop Policies

Courses may be added and dropped through the end of the Add/Drop period for the individual class. After the first week of class you must receive an Add Restriction override from the instructor if you wish to add a course. The specific Add/Drop deadline for each course is listed on the online Class Schedule or on your My Weekly Schedule on RAMweb . When an on-campus course is dropped, any charges associated with the course are refunded. For refunds associated with Continuing Education online courses, please go to CSU Online.

Dropping a course

How to Drop an Online Course     University Withdrawal / Dropping Your Last Online Course

How to Drop an Online Course    

Drops must be requested through one of the methods below; no drops can be completed via telephone.

Online:

RAMweb and click on "Registration" to get started. If you are dropping your last course, you cannot use RAMweb. You must email or fax your drop request.

Email:

Send an email to csu_online_registration@mail.colostate.edu and include your name, CSUID, and the course(s).

Fax:

(970) 491-7885

You will receive confirmation of your course changes. It is your responsibility to retain registration documents as proof of course changes.

University Withdrawal / Dropping Your Last Online Course

A University Withdrawal constitutes a drop from all of your courses and departure from the University, which is different from dropping one or more courses. If you choose to drop your last course and withdraw from the University you will also be dropped from your degree program and must be readmitted before any future credits or grades will apply to your degree. It is important that you speak with your departmental advisor about the impact to your degree, academic requirements, and re-admittance policies (undergraduate policy | graduate policy).

University Withdrawals are not available during the summer semester.

If you are a graduate student, you may opt for Continuous Registration and not be dropped from your degree program for the semester.

Withdrawing from the University does not eliminate your financial obligations to the University. You are responsible for any charges owed to the University at the time you withdraw as determined by the drop and refund policy. Withdrawing from the University will impact your financial aid.

University fees will be refunded if the University Withdrawal occurs prior to the first week of class.

Resources

RAMweb

RAMweb provides online access to application status, registration, financial information, personal records, jobs, and more for applicants, new, and current students.

Log in to RAMweb

Canvas

Colorado State University uses Canvas by Instructure as its online learning management system (LMS). Use Canvas to interact with your instructor and other students, learn from the course materials, participate in discussions, submit assignments, take tests and view grades. To log in to Canvas and see your courses, you must have an active CSU eID account, and be registered for a class.

Log in to Canvas

eID

Colorado State University's Electronic Identity (eID) system facilitates a simplified and secure form of authentication and authorization across multiple university electronic systems and services. Go here for more information.

Software

RamTech is the on-campus software provider. It is worth checking their price because CSU subsidizes a number of 'site licenses' for commonly used software, such as SAS, which may reduce or eliminate the price. However, in some cases, you may be better off visiting a retailer near you, such as Office Depot or Best Buy, or visiting a retail software website.

R is available by free download. This page includes information on obtaining a free download of R for your computer.

Textbooks

The CSU Bookstore sells both new and used textbooks for our online courses; however, you may order your books from whatever source you wish. Other sellers might include a university bookstore near you, or several online retailers.

Detailed STAA Course Listing

STAA551: Regression Models and Applications 02 Credits.

Prerequisite: Admission to the MAS program or written consent of instructor. 

Estimation and hypothesis testing methods in linear models including t-tests, ANOVA, regression, including multiple regression. Residual analyses, transformations, goodness of fit, interaction and confounding. Implementation in SAS and R.

Textbook: TBD

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on bi-weekly homework sets, a proctored mid-term exam, and a proctored cumulative final exam.

Credit allowed for only one course: STAT540, STAT512, STAA551

Note: This course is approved by the Society of Actuaries for the regression component of the Validation by Educational Experience (VEE).


STAA552: Generalized Regression Models 02 Credits.

Co-requisite: STAA551 and STAA561. 

Nonlinear regression, iteratively re-weighted least squares, dose-response models, count data, multi-way tables, survival analysis.

Textbook: Categorical Data Analysis, 3rd ed., by Alan Agresti (Wiley Series in Probability and Statistics 978-0-470-46363-5).

Computer Software: R and SAS.

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on six homework sets, two proctored quizzes and a proctored final exam.

Credit allowed for only one course: STAT645, STAA552


STAA553: Experimental Design 02 Credits.

Prerequisite: STAA551 and STAA562. 

Analysis of variance, covariance, randomized block, latin square, split-plot, factorial, balanced and unbalanced designs. Applications to agriculture, biosciences. Implementation in SAS and R

Textbook: Textbook Optional - Design and Analysis of Experiments with SAS, by John Lawson (Chapman and Hall/CRC, ISBN-10: 1420060600, ISBN-13: 978-1420060607)

Computer Software: R and SAS

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets, a proctored mid-term exam, and a proctored, cumulative final exam.

Credit allowed for only one of: STAT650 or [STAA553 and STAA554]


STAA554: Mixed Models 02 Credits.

Co-requisite: STAA552 and STAA553. 

Topics in linear, generalized linear, and nonlinear models with fixed and random predictors, balanced and unbalanced cases. Statistical topics will be integrated with the use of the computer packages SAS and R.

Textbook: to be determined

Computer Software: R and SAS.

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets, a proctored mid-term exam, and a proctored, cumulative final exam.

Credit allowed for only one of: STAT650 or [STAA553 and STAA554]


STAA556: Statistical Consulting 03 Credits.

Prerequisite: 28 credits of STAA coursework, or one year in the MS or PhD program.

Consultant-client interactions, communications, ethical practices. Complete a consulting project and provide a report.

Textbook: No textbook required.

Proctor: This course does not require an exam proctor.

Grading: Course grade is based on class assignments and a formal consulting project.

Credit allowed for only one course: STAT586, STAA556

 

STAA561: Probability with Applications 02 Credits.

Prerequisite: Admission to the MAS program or written consent of instructor. 

Random variables, continuous and discrete distributions, expectations, joint and conditional distributions, transformations. Applications to capture/recapture, financial and industrial models.

Textbook: No textbook required.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets, three proctored (bi-weekly) quizzes, and a proctored cumulative final exam.

Credit allowed for only one course: STAT520, STAA561


STAA562: Mathematical Statistics with Applications 02 Credits.

Co-requisite: STAA561

Theory and applications of estimation, testing, and confidence intervals. Computer simulations; sampling from the normal distribution.

Textbook: No textbook required.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets, three proctored (bi-weekly) quizzes, and a proctored cumulative final exam.

Credit allowed for only one course: STAT530, STAA562


STAA565: Quantitative Reasoning 01 Credit.

Co-requisite: STAA551

Confounding, types of bias such as selection bias and regression effect bias, Simpson’s paradox, experiments versus observational studies, etc.

Textbook: No textbook required.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets and three proctored quizzes.


STAA566: Computational and Graphical Methods 01 Credit.

Prerequisite: Admission to the MAS program or written consent of instructor. 

Exploratory data analysis using graphics, effective communication with graphs, data reduction methods.

Textbook: Graphics for Statistics and Data Analysis with R, by Kevin J. Keen (Chapman and Hall/CRC 978-1584880875).

Computer Software: R

Proctor: This course does not require an exam proctor.

Grading: Course grade is based on bi-weekly homework sets.

Credit allowed for only of: STAT600 or [STAA566 and STAA567]


STAA567: Computational and Simulation Methods 01 Credit.

Co-requisite: STAA551 and STAA561

Sampling methods, simulating distributions of test statistics, optimization.

Textbook: No textbook required. Students may want to use as a reference: Computational Statistics by James Gentle, ISBN-10: 0387981438 | ISBN-13: 978-0387981437.

Computer Software: R

Proctor: This course does not require an exam proctor.

Grading: Course grade is based on homework assignments.

Credit allowed for only one of: STAT600 or [STAA566 and STAA567]

 

STAA568: Topics Industrial/Organizational Statistics 01 Credit.

Co-requisite: STAA553 and STAA561 or written consent of instructor.

This course will focus on a quality improvement methodology called Lean Six Sigma.  The Six Sigma roadmap – DMAIC – and Lean concepts will be covered and applied to a hands on project that students will select and execute during the class.  The best way to learn this approach is by applying the tools to real life projects.  We will conduct class on two Saturdays, with two weeks between classes.

Textbooks:

  • Six Sigma Memory Jogger II: A Pocket Guide, by Brassard, Finn, Ginn & Ritter (ISBN 10: 1576810445 , ISBN 13: 9781576810446 )
  • The Lean Six Sigma Pocket Toolbook: A Quick Reference Guide to 100 Tools for Improving Quality and Speed, by George, Maxey, Rowlands & Price (ISBN-10: 0071441190, ISBN-13: 9780071441193)
  • Access to the STAA 553 text: Design and Analysis of Experiments with SAS, by John Lawson (Chapman and Hall/CRC, ISBN-10: 1420060600, ISBN-13: 978-1420060607) or a similar design of experiments text.

Computer Software: The course will cover use of Minitab software.  Minitab 17 Student Version can be purchased here. Minitab 16 may be used if you already have it. This software is not required, but it is in widespread use and includes routines in the software that facilitate using the DMAIC tools.

Proctor: This course does not require an exam proctor.

Grading: Course grade is based on a course project.

Credit allowed for only one course: STAT547, STAA568


STAA571: Survey Statistics 02 Credits.

Prerequisite: STAA551 and STAA562

Estimation and variance estimation for complex survey designs, accounting for stratification, clustering, and unequal probabilities of selection.  Taught jointly with STAT605 in alternate years. 

Textbook: Applied Survey Data Analysis, Steven G. Heeringa, Brady T. West, Patricia A. Berglund
ISBN 978-1-4200-8066-7 Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

Computer Software: R (required).

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on homework sets, a proctored mid-term exam, and a proctored cumulative final exam.

Credit allowed for only one course: STAT605, STAA571

 

STAA572: Nonparametric Methods 02 Credits.

Co-requisite: STAA551 and STAA561

Rank-based methods, nonparametric inferential techniques, scatterplot smoothing, nonparametric function estimation, environmental applications.

Textbook: Introduction to Modern Nonparametric Statistics, by James J. Higgins (Cengage ISBN:9780534387754)

Computer Software: R

Proctor: This course does not require an exam proctor.

Grading: Course grade is based on homework sets, two mid-term exams, and a final exam.

Credit allowed for only one course: STAT570, STAA572


STAA573: Analysis of Time Series 02 Credits.

Co-requisite: STAA551 and STAA561

Moving average and auto-regressive correlation structures, estimation and forecasting, modeling seasonality. Financial and environmental applications.

Textbook: Time Series Analysis and Its Applications: With R Examples, 3rd ed., by Shumway & Stoffer.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on homework sets, a proctored mid-term exam, and a proctored cumulative final exam.

Credit allowed for only one course: STAT525, STAA573.

Note: This course is approved by the Society of Actuaries for the time series component of the Validation by Educational Experience (VEE).


STAA574: Methods in Multivariate Analysis 02 Credits.

Prerequisite: STAA 551 and STAA561. Note: R programming skills are expected, as well as strong knowledge of linear algebra.

Multivariate ANOVA, principal components, factor analysis, cluster analysis, discrimination analysis.

Textbook: Applied Multivariate Statistical Analysis, 6th ed., by Johnson & Wichern.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on homework sets, a proctored mid-term exam, and a proctored cumulative final exam.

Credit allowed for only one course: STAT560, STAT460, STAA574


STAA575: Applied Bayesian Statistics 02 Credits.

Prerequisite: STAA552, STAA562 and STAA567. 

Bayesian analysis of statistical models, prior and posterior distributions, computing methods, interpretation.

Textbook: Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians, by Christensen, Johnson, Branscum & Hanson.

  • ISBN-10: 1439803544
  • ISBN-13: 978-1439803547

Computer Software: R and either openBUGS (available at http://www.openbugs.net/w/FrontPage) or JAGS (Mac users will prefer JAGS, http://mcmc-jags.sourceforge.net/

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on homework sets and a proctored cumulative final exam.

Credit allowed for only one course: STAT675K, STAA575


STAA576: Methods in Environmental Statistics 02 Credits.

Prerequisites: STAA552 and STAA561. Note: R programming skills are expected.

This course will introduce a number of statistical methodologies that are used in environmental and ecological studies. Students are introduced to topics in spatial statistics, and abundance estimation for biological populations.

Textbook: Course notes will be provided.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on homework sets, a proctored mid-term exam, and a proctored cumulative final exam.

Credit allowed for only one course: STAT523, STAA576


STAA577: Statistical Learning and Data Mining 02 Credits.

Prerequisites: STAA551 and STAA561. Note: R programming skills are expected.

Regularization, prediction, regression, classification and clustering. Students will learn to implement modern statistical techniques for analyzing the types of data that would be encountered by statisticians working in business, medicine, science and government.

Textbook: An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics), by James, Witten, Hastie & Tibshirani. ISBN-13: 978-1461471370, ISBN-10: 1461471370.

Computer Software: R

Proctor: This course requires an approved proctor for exams. Submit proctor information here.

Grading: Course grade is based on weekly homework sets, three proctored (bi-weekly) quizzes, and a proctored cumulative final exam.

Note: This course is allowed in place of STAA576 for the MAS degree.

Other Course Listings

 

GSLL 3095 Math Skills for Statistical Analysis (MSSA)

Intensive review of mathematical methods that will be used in the MAS program, including but not limited to differential and integral calculus, chain rule, l'Hôpital's rule, integration by parts, Taylor's theorem, multiple integrals, sequences and series, limits, linear algebra, matrix theory. Not for credit. Course will be offered during Sub-term 1 of the MAS (during the 8-week Summer term for online students).

Textbook: No formal text is required; however, students should have access to texts on multivariate calculus and linear algebra for reference. There will be a handout given for each topic, available to print from RamCT.  If you do wish to purchase a text, you may want to consider the Schaum's outlines for these topics:

Schaum’s Outline of Linear Algebra, 5th Edition. ISBN-13: 978-0071794565
Schaum’s Outline of Calculus, 6th Edition. ISBN-13: 978-0071795531

Don't spend a lot of money. We want to emphasize that any standard calculus and linear algebra texts will suffice. 

Computer Software: None required.

Notes:

  1. Although required for the MAS program, this is a noncredit course. Grades are not issued for noncredit courses. Noncredit courses do not appear on Colorado State University academic transcripts and are not eligible for financial aid. However, the Statistics Department will provide a 'letter of completion' upon request to students who can demonstrate that they have completed all course components. Students who are seeking reimbursement for tuition should check with their employer before registering for this course.
  2. This course is intended to be a review of the math skills needed for the MAS program, delivered in a statistical context. Before taking this class, students should have already taken courses in single- and multi-variable calculus and linear algebra.
  3. At the end of this course, students will be given a proctored 'final exam'. The exam is graded, but the grade only serves the purpose of informing students of their preparedness for the MAS or Certificate in Applied Statistics coursework. Students will need to secure an approved proctor for the exam.

 

GSLL 3096 Computing Skills for Statistical Analysis (CSSA)

Software packages, graphics and programming using R, SAS and other popular packages; review of introductory statistics. Not for credit. Course will be offered during Sub-term 1 of the MAS (the 8-week Summer term for online students), as well as Sub-term 4 of the MAS (the first 8 weeks of the Spring semester).

Textbook: No textbook required. Students will download a free manual to use for R computing.

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.

Note: Although required for the MAS program, this is a noncredit course. Grades are not issued for noncredit courses. Noncredit courses do not appear on Colorado State University academic transcripts and are not eligible for financial aid. However, the Statistics Department will provide a 'letter of completion' upon request to students who can demonstrate that they have completed all course components. Students who are seeking reimbursement for tuition should check with their employer before registering for this course.

 

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.

 

CSU Online Course Registration

To view a list of STAA courses offered through CSU Online, click here

GS6 Form

The Program of Study (GS6) is a document which must list all the required courses (taken and planned) to achieve your degree. The Program of Study must be filed with the Graduate School before the time of the fourth regular semester registration. Students who fail to meet this requirement may be denied subsequent registration. In addition, this form must be submitted to the Graduate School prior to applying for graduation.

How to complete the form

In order to complete the GS6 form, you can log onto RamWeb using your eID.  The form is completed electronically.  You will need to print the completed form, sign it and get it to us by fax or e-mail for departmental signature.  Fill in the information below and use this to complete your GS6 form.  If you have questions, please contact Karena Topf at topf@stat.colostate.edu. 

CSU ID: __________________
Program Code: MAST-DD-MAS (Online students) or MAST-MAS (On-Campus students)
Degree: Master of Applied Statistics
Program: Master of Applied Stat/Distnce
Admit Term: ____________
Site: DD – Online-distance (Online students only)

Required Courses Taken Prior to Admission
This section will be empty, unless you took courses prior to your formal admission into the MAS program.  Any STAA courses that you completed through CSU prior to your semester of admission will go in this section.   

Required Courses Taken After Admission
Enter all course you will take to earn your MAS degree, except those taken prior to admission.  Your combined list of courses (prior and after admission), unless you have transfer courses, must include the following:

  • STAA551, STAA552, STAA553, STAA554, STAA556
  • STAA561, STAA562, STAA565, STAA566, STAA567, STAA568
  • STAA571, STAA572, STAA573, STAA574, STAA575, STAA576 OR STAA577

Be sure to check that the number of credits listed for each course is correct.  STAA 556 is 3 credits; STAA 565, STAA 566, STAA 567 and STAA 568 are all 1 credit; and the remaining courses are all 2 credits.

You must fill in a total of at least 31 credits (including Prior and After admission courses) to fulfill the requirements listed above.  Check with Jana Anderson if you have any questions regarding the course requirements, or if you are applying any transfer or STAT prefix courses to the MAS. 

If a master’s degree is to be used as part of the Ph.D. program, fill in the following information
This portion will be left blank.

Transfer of Specific Course Credit from Other Institutions  
Complete this portion only if you have approved transfer coursework.  If you have any questions regarding course substitutions for transfer coursework, please contact Jana Anderson.

Non-Course Requirements
This section will be auto-filled.

Committee 
The MAS degree is a Plan C master’s, so you will only need to specify an advisor.  The advisor for all MAS students is Jana Anderson.

Once you have submitted the GS6 form, you need to print it, sign it and send an electronic copy to Karena Topf at topf@stat.colostate.edu.

Final Term and Graduation

The MAS program concludes in the summer term with the capstone consulting course (STAA 556). The Graduate School does not offer a commencement ceremony during the summer term. MAS graduates can choose to walk in the spring commencement ceremony prior to the completion of the program or the fall commencement ceremony following completion of the program. To be eligible to graduate, a student must have successfully completed all of the requirements for the MAS program and submit an Application for Graduation (GS25) form. (The GS25B form is not required for MAS students.) A student applying to graduate can start the process using the "Apply or Reapply to Graduate" link in RAMweb.

The Graduate Commencement Ceremony is held at 3 pm in Moby Arena on the Friday of Finals Week each spring and fall semester. Visit the Graduate School's Commencement page for more details.  

 

Employment

Winter and early spring is a good time to start working on your resume.  You will want to include any information you think may be important to potential employers.  You may also want to think about getting your SAS certification during this time, so that you'll have it before it's time to interview.  Check with Karena Alons (alons@stat.colostate.edu) for details regarding SAS certification. 

For information on career paths, including job requirements and responsibilities, salary figures, and interviews with current professionals in the Data Science field, click here.

For more information on the Master of Applied Statistics program, please contact the statistics department at (970) 491-5268 or by email at stats@stat.colostate.edu

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