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The Statistics certificate is a great fit for students who wish to use statistical principles to solve data problems with a mathematical approach. Students will develop knowledge and skills in analytics and statistics, such as understanding how to work with data and applying their analysis within their given major or domain area. Statistics continues to be one of the fastest growing employment sectors in the nation and in Wisconsin and the Statistics certificate will allow a broader range of students to gain these highly desired skills.

Students in the certificate will gain “scientific, professional and technological expertise, and a sense of purpose.”

How to Get in

Students must have credit for the following to declare the certificate:

Complete one introductory statistics course
Applied Statistics for Biomedical Engineers
Statistics: Measurement in Economics
Introduction to Industrial Statistics
Data Science Modeling I
Introduction to Statistical Methods
Introductory Applied Statistics for Engineers
Introductory Applied Statistics for the Life Sciences
Complete one calculus course
Survey of Calculus
Calculus and Analytic Geometry 1
Calculus with Algebra and Trigonometry I
and Calculus with Algebra and Trigonometry II

Information on how to declare the certificate is available on our website. Students are encouraged to schedule a meeting with a Statistics advisor if they have questions.

Students declared in the Statistics major or Data Science major are not eligible to declare this certificate.

Requirements

The certificate requires a minimum of 13 credits.

Introductory Statistics, complete one option3-4
Applied Statistics for Biomedical Engineers
Statistics: Measurement in Economics
Introduction to Industrial Statistics
Data Science Modeling I
Introduction to Statistical Methods
Introductory Applied Statistics for Engineers
Introductory Applied Statistics for the Life Sciences
Statistical Language1
R for Statistics I
Regression Analysis, complete one option3-4
Applied Regression Analysis
Data Science Modeling II
Probability, complete one option3
Introduction to Random Signal Analysis and Statistics
Introduction to Probability and Mathematical Statistics I
Introduction to Theory and Methods of Mathematical Statistics I
Introductory Probability
Introduction to the Theory of Probability
Probability Theory
Elective, complete one option3
R for Statistics II
R for Statistics III
Introduction to Probability and Mathematical Statistics II
Introduction to Theory and Methods of Mathematical Statistics II
Introduction to Time Series
Introductory Nonparametric Statistics
Data Science Computing Project
An Introduction to Sample Survey Theory and Methods
Applied Categorical Data Analysis
Statistical Experimental Design
Data Science with R
Statistical Data Visualization
Classification and Regression Trees
Introduction to Machine Learning and Statistical Pattern Classification
Introduction to Deep Learning and Generative Models
Applied Multivariate Analysis
Financial Statistics
Introduction to Computational Statistics
Special Topics in Statistics
Statistical Methods for Spatial Data
Statistical Methods for Clinical Trials
Statistical Methods for Epidemiology
Total Credits13

Residence and Quality of Work

  • At least 7 certificate credits must be completed in residence
  • Minimum 2.000 GPA on all certificate courses

Certificate Completion Requirement  

This undergraduate certificate must be completed concurrently with the student’s undergraduate degree. Students cannot delay degree completion to complete the certificate.

Learning Outcomes

  1. Frame a scientific question with the appropriate mode of data analysis, analyze such data correctly, and summarize and interpret the results in a useful manner
  2. Apply a number of key statistical techniques, including significance testing, goodness-of-fit testing, and regression analysis
  3. Use tools from mathematical statistics and probability to assess the quality of point estimators, confidence intervals, and hypothesis tests
  4. Apply a statistical language to manipulate data and perform exploratory data analysis using basic statistical methods

Advising and Careers

Students who are interested in statistics academic advising should check out the advising information on our website or send an email to statcert@stat.wisc.edu

Please note that students will need at least MATH 213 or MATH 222 to finish the Statistics certificate requirements.

L&S Career Resources

Every L&S major opens a world of possibilities. SuccessWorks at the College of Letters & Science helps students turn the academic skills learned in their major, certificates, and other coursework into fulfilling lives after graduation, whether that means jobs, public service, graduate school, or other career pursuits.

In addition to providing basic support like resume reviews and interview practice, SuccessWorks offers ways to explore interests and build career skills from their very first semester/term at UW all the way through graduation and beyond.

Students can explore careers in one-on-one advising, try out different career paths, complete internships, prepare for the job search and/or graduate school applications, and connect with supportive alumni and even employers in the fields that inspire them.

People

A full listing of the Statistics faculty, including affiliated faculty and links to webpages, can be found on the departmental website.

Faculty

  • Cecile Ane, Professor, Statistics and Botany
  • Joshua Cape, Assistant Professor, Statistics
  • Peter Chien, Professor, Statistics
  • Jessi Cisewski-Kehe, Assistant Professor, Statistics
  • Sameer Deshpande, Assistant Professor, Statistics
  • Nicolas Garcia Trillos, Assistant Professor, Statistics
  • Yinqiu He, Assistant Professor, Statistics
  • Hyunseung Kang, Assistant Professor, Statistics
  • Sunduz Keles, Professor, Statistics & Biostatistics and Medical Informatics
  • Bret Larget, Professor, Statistics
  • Keith Levin, Assistant Professor, Statistics
  • Wi-Yin Loh, Professor, Statistics
  • Michael Newton, Professor, Statistics & Biostatistics and Medical Informatics
  • Vivak Patel, Assistant Professor, Statistics
  • Alejandra Quintos, Assistant Professor, Statistics
  • Sebastian Raschka, Assistant Professor, Statistics
  • Garvesh Raskutti, Associate Professor, Statistics
  • Karl Rohe, Professor, Statistics
  • Kris Sankaran, Assistant Professor, Statistics
  • Jun Shao, Professor, Statistics
  • Miaoyan Wang, Assistant Professor, Statistics
  • Yazhen Wang, Chair and Professor, Statistics
  • Brian Yandell, Professor, Statistics
  • Chunming Zhang, Professor, Statistics
  • Zhengjun Zhang, Professor, Statistics
  • Yiqiao Zhong, Assistant Professor, Statistics
  • Jun Zhu, Professor, Statistics