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  • MS in Biostatistics
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MS in Biostatistics

This program emphasizes the applied and theoretical nature of biostatistics. In addition to courses on theory, statistical computing, consulting, analysis of clinical trials, and longitudinal and survival data, you'll be exposed to a wide variety of research areas including statistical genetics and genomics, causal inference, infectious disease, and cancer research. During the program, you’ll get involved in research with a faculty mentor as part of your thesis or research paper. You'll also have the opportunity to specialize in one of two minor areas within the MS—Statistical Genomics and Data Science Analytics. 

Application and deadline

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Tuition and aid

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Quick facts, careers, and skills

When you graduate with an MS in Biostatistics, you’ll be ready for a career designing and analyzing clinical trials and public health studies.

Quick facts

Program location: CU Anschutz
Est. time to complete: 2 years
Credit hours: 36
Option: Minor in Statistical Genomics/Genetics or Data Science Analytics

Sample careers

Biostatistician
Data analyst
Data scientist
& more


Skills you'll gain

Data visualization
Collaborative research
Statistical programming
& more


Curriculum


This program will prepare you for in-depth study and research in statistics as it applies to healthcare and biological settings. You'll get a balance between theory, methods, and hands-on practical and research experience. Our required courses include applied and theoretical statistics, statistical computing, consulting, and advanced statistical modeling. Plus, you can choose elective coursework ranging from analysis of clinical trials to survival analysis to statistical ‘omics. You'll also complete a Master's research paper or thesis.

In addition, we offer two minor areas of specialization within the MS—Statistical Genomics and Data Science Analytics. We recommend planning out the minor in your first year to ensure timely graduation and availability of electives. Check out the Department of Biostatistics & Informatics FAQ page for more information about this program.

Examples of thesis titles and research conducted by past students can be found at the bottom of the department's students page.

Course requirement
Course ID
Credits
Biostatistical Methods I
BIOS 6611
3
Biostatistical Methods II
BIOS 6612
3
Statistical Consulting I
BIOS 6621
1
​Statistical Consulting II
BIOS 6622​1
​Advanced Statistical Methods & Analysis
BIOS 6624
3
Statistical Theory I
BIOS 6631​
3
​Statistical Theory II
BIOS 6632​
3
​Longitudinal Data Analysis
BIOS ​66433
  20

 

Course requirement
 Course ID
 Credits
​Foundations in Public Health  PUBH 6600​2
Public Health Concepts EHOH 66011
​EpidemiologyEPID 6630​3
  6

Students are required to take 6 credits from this list below. Courses not listed require director approval; additional PhD electives can be found on the PhD webpage and may be used with director approval.

Course requirement

Course ID

Credits

Causal Inference
BIOS ​66413
​Introduction to Python Programming
BIOS ​66422
​Predictive Analytics
BIOS ​66453
​Survival Analysis
BIOS 6646​3
Design of Studies in Health Sciences
BIOS 6649​3
​Analysis of High-throughput DataBIOS 6660​3

 

Course requirement

Course ID

Credits

MS Thesis or MS Research Paper

BIOS 6950 or BIOS 6651

4

 

Total credits: 36

Sample schedule

The following sample schedule is designed to help you plan your courses. The number of credits in a given semester, the order in which the required courses are taken, and the courses you take to meet the concentration requirements may vary. ​Please note that you cannot use the same course to fulfill more than one requirement. The MS in Biostatistics degree is designed to be completed in two academic years.

Year 1 FallYear 1 SpringYear 1 Summer

BIOS 6611 (3 credits)

BIOS 6631 (3 credits)

BIOS 6621 (1 credit)

CSPH Required PH (1 credit)

BIOS 6612 (3 credits)

BIOS 6632 (3 credits)

BIOS 6622 (1 credit)

PUBH 6600 (2 credits)

 

Year 2 FallYear 2 Spring

BIOS 6624 (3 credits)

BIOS 6643 (3 credits)

EPID 6630 (3 credits)

MS Elective (3 credits)

MS Elective (3 credits)

MS Thesis/Research Paper (4 credits)

 

View the course book and course schedule >

Competencies

IdentifierCompetencies
MS-BIOS 1
Carry out and explain calculations, derivations and proofs central to basic statistical theory, and explain their use and implications in applied statistical work.
MS-BIOS 2
Apply statistical concepts of basic study designs including bias, confounding and efficiency, and identify strengths and weaknesses of experimental and observational designs.
MS-BIOS 3
Carry out exploratory and descriptive analyses of complex data using standard statistical software and methods of data summary and visualization.
MS-BIOS 4Carry out valid and efficient modeling, estimation, model checking and inference using standard statistical methods and software.
MS-BIOS 5Demonstrate statistical programming proficiency, good coding style and use of reproducible research principles using leading statistical software.

 

IdentifierCompetencies
MS-BIOS 6
Demonstrate basic skills necessary for collaborating with non-biostatistical scientists, including mapping study aims to testable hypotheses, carrying out basic power and sample size estimation and evaluation, and identifying appropriate design, modeling and analysis methods to address study hypotheses.
MS-BIOS 7
Communicate, orally and in writing, simple and complex statistical ideas, methods and results in non-technical terms appropriate for collaborator needs (e.g. preparation of analysis section of grant proposals and methods and results sections of manuscripts).

 


Minor in Statistical Genomics & Genetics


We offer two minors—small, optional groupings of courses—that are designed to provide specialization for the MS degree on a certain topic. The Statistical Genomics & Genetics minor, offers an official designation in a topic that has become very popular within the field of biostatistics and is a strength of our program that will help you with employment and other opportunities.

MS students and PhD students who are in the process of obtaining a MS degree are eligible. It is best to plan out the minor starting the first year to ensure timely graduation.

  1. Take an additional 3 credits of electives; 6 of the elective credits must be from a list of courses related to statistical genetics/genomics; at most 4 credits may be from an outside department.
  2. Write a thesis or publishable paper with a focus on Statistical Genomics & Genetics.

The MS in Biostatistics degree is designed to be completed in two academic years. Although the minor requires three additional credits for the specialization, the degree can still be completed within two years assuming students take courses over the summer. See an example timeline below (individual cases and offerings every year will vary).

Year 1 Fall

Year 1 Spring

Year 1 Summer

BIOS 6611 (3 credits)

BIOS 6631 (3 credits)

BIOS 6621 (1 credit)

CSPH Required PH (1 credit)

BIOS 6612 (3 credits)

BIOS 6632 (3 credits)

BIOS 6622 (1 credit)

MS Minor Elective (1-4 credits)

 

PUBH 6600 (2 credits)

Year 2 FallYear 2 SpringYear 2 Summer

BIOS 6624 (3 credits)

BIOS 6643 (3 credits)

MS Minor Elective (1-4 credits)

MS Minor Elective (1-4 credits)

EPID 6630 (3 credits)

MS Thesis/Research Paper (2 credits)

MS Thesis/Research Paper (2 credits)

Course name
Course ID
Credits
R for Data ScienceBIOS 664022
Introduction to Python ProgrammingBIOS 664222
Analysis of Biomedical Big Data Using R & BioconductorBIOS 66603
Statistical Methods in GenomicsBIOS 76593
Topics in Probability and Statistics: Methods in Statistical GeneticsMATH 78263
Genetic Epidemiolo​gyEPID 764012
Computational Methods for Addressing Big Data Challenges in Biomedicine ICPBS 763013
Methods and Tools in Biomedical InformaticsCPBS 771114
Graduate Survey of Human GeneticsHMGP 760013
Topics in Human GeneticsHMGP 761013
Advanced Genome AnalysisHMGP 762012
R for BioinformaticsMOLB 79001 22
Python for BioinformaticsMOLB 79501 22

1  At most 4 credits can be taken from an outside program
2 Only one programming course may be taken

Please confirm with the program directors about your schedule and minor electives.

Minor in Data Science Analytics


In response to a changing landscape of biomedical research that relies more and more on the generation, analysis, and interpretation of large data sets, we offer a minor in Data Science Analytics. Students pursuing this minor within their MS in Biostatistics will have an official designation that will help with employment and other opportunities upon graduation.

MS students and PhD students who are in the process of obtaining a MS degree are eligible. It is best to plan out the minor starting the first year to ensure timely graduation and availability of electives.

  1. Take at least 9 credits of electives from a list of courses related to Data Science Analytics (see below). There are additional elective credits required in the minor compared to the original MS degree, so that there is opportunity to specialize in this area.
  2. Write a thesis or publishable paper with a focus on Data Science Analytics.

The MS in Biostatistics degree is designed to be completed in two academic years. Although the minor requires additional credits for the specialization, the degree can still be completed within two years assuming students take courses over the summer.  See an example timeline below (individual cases and offerings every year will vary).

Year 1 Fall

Year 1 Spring

Year 1 Summer

BIOS 6611 (3 credits)

BIOS 6631 (3 credits)

BIOS 6621 (1 credit)

CSPH Required PH (1 credit)

BIOS 6612 (3 credits)

BIOS 6632 (3 credits)

BIOS 6622 (1 credit)

MS Minor Elective

(3 credits)

PUBH 6600 (2 credits)

Year 2 FallYear 2 SpringYear 2 Summer

BIOS 6624

(3 credits)

BIOS 6643

(3 credits)

MS Minor Elective

(3 credits)

MS Minor Elective

(3 credits)

EPID 6630 (3 credits)

MS Thesis/Research Paper (2 credits)

MS Thesis/Research Paper (2 credits)

Course name
Course ID
Credits
Practical Clinical InformaticsBIOS 631013
R for Data ScienceBIOS 664022
Introduction to Python ProgrammingBIOS 664222
Practical Data WranglingBIOS 664412
Predictive AnalyticsBIOS 66451 33
Data Management Using SASBIOS 66803
Structured Query Language (SQL)BIOS 668111
Intro Public Health InformaticsBIOS 668513
Statistical and Machine LearningMATH 63881 33
Data MiningCSCI 4455/54553
Data ScienceCSCI 4580/55803
Machine LearningCSCI 4930/59303
Deep LearningCSCI 4931/59313
Big Data SystemsCSCI 4951/59513
Big Data MiningCSCI 5950/79503
Big Data ScienceCSCI 5952/79523
Object-Oriented Programming231323
Data Structures & Program DesignCSCI 242123
Database System Concepts328723
AlgorithmsCSCI 34122 

1  At least 3 BIOS credits should be taken

2 Only one lower-level 2000/3000 CSCI course can count towards the electives, these are used to meet prerequisites of the 5000 CSCI series if needed

3 Because of overlap, only MATH 6388 or BIOS 6645 can be counted as an elective

Your minor degree plan is subject to approval by the program director(s), please check with them before enrolling in minor electives

Support from the department


This program is designed to be completed in two years by full time students. Many MS students are supported through research or teaching assistantship positions. These positions are competitive and offer opportunities for training and experience in research, teaching, and practice in biostatistics. During the past several years more than half of MS students were supported in some way upon entry to the program, and all students were supported in research positions by the end of their first summer. Through these positions students gain real-world research and collaborative experience on a very large and active health sciences campus. This practical experience is a strength of our program.

Colorado School of Public Health

CU Anschutz

Fitzsimons Building

13001 East 17th Place

3rd Floor

Mail Stop B119

Aurora, CO 80045


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