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Statistical Science

M.S. Statistics

» Department of Statistical Science   » College of Science


  • INTRODUCTION
  • WHAT IT TAKES
  • WHAT PEOPLE DO
  • GET INVOLVED
  • FACULTY
students working on stats problems

With a Master of Science (M.S.) in Statistical Science, you'll learn to effectively apply statistical principles and data analysis in a number of diverse industries. Or, you may choose to teach statistics at the high school (teacher certification is required) or community college level.

An advanced degree in statistics opens doors to an infinite number of career opportunities. Because of the applied nature of statistics, you may begin your studies with a bachelor’s degree in a related program, such as business, biological sciences or chemistry. Our program gives you an understanding of the broad applications and theoretical aspects of statistics, allowing you to explore relationships among variables in your chosen field.

For example, with an undergraduate degree in biological sciences or health sciences and a graduate degree in Statistical Science, you may build a successful career with a pharmaceutical company where you develop experiments and apply statistical methods to prove a drug is ready for the final stages of FDA testing. Or, with a background in economics, you may use your master's degree in statistics to build a career in market research, business analysis or forecasting.


The University of Idaho Department of Statistical Science is made up of an interdisciplinary team of dedicated faculty from business, geography, fish and wildlife resources, economics and more. Depending on your research interest area, you will be assigned a faculty member to act as your adviser. This faculty member will help formulate a study plan designed specifically to meet your goals and to guide you through the program. Topics you may explore include:

  • Applying mathematical principles to the collection, analysis and presentation of numerical data.
  • Designing and analyzing experiments.
  • Planning and interpreting surveys.
  • Exploring relationships among variables.


Group projects and research opportunities with faculty, local businesses and government agencies will give you experience you can apply immediately on the job.


Stats students

Prepare for Success

To be successful in our program, you should have strengths in quantitative methods and have the ability to analyze data to make decisions which are part of a larger goal. In addition to working in labs and in an office environment, you should also know how to use computers for statistical modeling and to summarize and analyze findings. Specific prerequisites needed to enter our master's program include:

  • Three semesters of calculus.
  • Six hours of statistics, including Stat 431(formerly Stat 401): Statistical Analysis, or equivalent.
  • One computer programming course or the demonstrated ability to write programs.


Your First Year

Required subjects include differential and integral calculus, statistical methods, mathematical modeling and probability theory. Graduate statistics courses include:

  • Sample Survey Methods (422)
  • Probability Theory (451)
  • Mathematical Statistics (452)
  • Seminar (501)
  • Experimental Design (507)
  • Non-parametrics (514)
  • Multivariate Analysis (519)
  • Consulting Practicum (597)


What You Can Do

With a Master of Science in Statistics, you may become a:

  • Secondary statistics teacher
  • Teacher at the community college level
  • Economist
  • Computer programmer
  • Software engineer
  • Actuary
  • Financial analyst
  • Research and development manager
  • Quality assurance engineer


Opportunities

The federal government and state agencies are always looking for graduates with an advanced statistics degree. In private industry, those with a statistics background are sought out particularly by organizations involved with scientific research and development services, insurance, and pharmaceutical and medical manufacturing companies. Employers who frequently hire individuals with a advanced statistics degree include:

  • Department of Commerce
  • Department of Agriculture
  • Department of Health and Human Services
  • Computer and hardware manufacturers
  • Pharmaceutical companies
  • Software and computer engineering firms
  • Financial planning or insurance agencies

According to the Bureau of Labor and Statistics, the median annual wage-and-salary earnings of statisticians was $72,830 and the average annual salary for statisticians in the federal government was $94,970 in 2011, while mathematical statisticians averaged $108,868.


Current Research

As well as being excellent educators, our faculty members are extremely active in research pursuits, with projects designed specifically around the involvement of students.


Activities

The Department of Statistics Applied Statistics in Agriculture Seminar Series and the Department of Mathematics Seminars & Colloquia explore important industry topics that will prepare you for success in your chosen career.


Hands-On Experience

Hands-on research efforts will give you exposure to real-world challenges you’ll face throughout your career.

A limited number of assistantships are available for on campus students.


Facilities

The University of Idaho has extensive research facilities, and in many cases our faculty have established relationships with professors at neighboring universities, which will give you access to even more high-tech equipment. Equipment and facilities, include:

  • A private computer lab containing three PC's running Windows 7 Professional.
  • Available software includes the most current versions of SAS, Minitab, SPSS, and R, as well as, other productivity software.
  • Student labs across campus are equipped with PC computers, MacIntosh computers, access to the university system of Unix workstations, laser printers and scanners.


Online & Outreach

You also have the option to earn a M.S. in Statistical Science through our distance education program, Engineering Outreach.



Zaid Abdo
Zaid Abdo, Ph.D.
Associate Professor
Here are the areas I am interested in, listed in order of interest: Bioinformatics, Statistical Genetics, Bayesian Statistics, Mathematical Biology, Stochastic Processes & Optimization
» View Zaid Abdo's profile.
Brian Dennis
Brian Dennis
Professor
Research interests: Statistical Ecology, Biometrics, Mathematical Modeling, Theoretical Ecology, Conservation Biology, Population Dynamics
» View Brian Dennis' profile
Paul Hohenlohe
Paul Hohenlohe, Ph.D.
Assistant Professor
Our research focuses on the genomic architecture of evolving populations, developing sophisticated theory and analytical tools to harness the power of modern DNA sequencing technology. We address basic questions of evolutionary biology as well as applications to conservation and cancer biology.
» View Paul Hohenlohe's profile
Timothy Johnson
Timothy R. Johnson, Ph.D.
Associate Professor, Affiliate Professor of Psychology
Currently, most of my research concerns ordinal variables and random utility models for categorical data. More broadly, I am interested in categorical data, latent variable models, measurement error models, simulation-based computations for inference, and Bayesian statistics. I sometimes collaborate in research in judgment and decision making.
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Paul Joyce
Paul Joyce, Ph.D.
Dean of College of Science & Professor
My research focuses on developing and rigorously testing statistical methods and stochastic models to describe genetic phenomena. These include models and methods to: predict how viruses adapt; show the effect of antibiotic resistance genes encoded on plasmids; predict ancestral relationships among species; and to understand the ecological structure of bacterial communities in biofilms. This broad focus has lead to collaborations with researchers in phylogenetics, population genetics, theoretical ecology, mircobial ecology, experimental evolution, conservation genetics, and the list is growing.
» View Paul Joyce's profile.
Stephen Sauchi Lee
Stephen Sauchi Lee, Ph.D.
Associate Professor
My general research area is Multivariate and Computational Statistics. It includes: Integrating models and methods from statistics, neural networks, machine learning, and data mining communities to discover relationships and recognize patterns in databases; modeling using regression and classification for interpretation and forecasting; extracting information and patterns; and developing computational algorithms to increase efficiency and prediction accuracy.
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Shafi
Bahman Shafii
Director of Statistical Programs and Professor

(208) 885-9498 | bshafii@uidaho.edu
» View profile
Michelle Wiest
Michelle Wiest, Ph.D.
Assistant Professor
Michelle’s research interests lie in epidemiological and biostatistical methods. Her work includes developing multivariate diagnostic and prognostic tools for evaluation of metabolic status, study design for nutrition interventions, and evaluation of risk factors for mining injuries. She plays a large role in supporting research across UI as a statistical consultant and in training master’s level statistics students in consulting.
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Christopher Williams
Christopher Williams, Ph.D.
Department Chair and Professor
Affiliate Professor of Bioinformatics and Computational Biology
My research interests are on problems in statistical genetics, biostatistics, and statistical methods applied to issues in natural resources. One of the topics that I work on is the analysis of human twin data. Another area of interest is the estimation of disease prevalence from various types of data, such as in groups of fish that are collected and have their tissue pooled to test for disease status.
» View Chris Williams' profile