Program Overview

Statistics, Certificate

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.

How to Get in

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

• Complete one introductory statistics course
  • B M E 325: Applied Statistics for Biomedical Engineers
  • ECON 310: Statistics: Measurement in Economics
  • I SY E 210: Introduction to Industrial Statistics
  • STAT 240: Data Science Modeling I
  • STAT 301: Introduction to Statistical Methods
  • STAT 324: Introduction to Statistics for Science and Engineering
  • STAT 371: Introductory Applied Statistics for the Life Sciences
• Complete one calculus course
  • MATH 211: Survey of Calculus 1
  • MATH 221: Calculus and Analytic Geometry 1
  • MATH 171 & MATH 217: Calculus with Algebra and Trigonometry I and Calculus with Algebra and Trigonometry II

Requirements

The certificate requires a minimum of 13 credits.

• Introductory Statistics (complete one course): 3-4 credits
  • B M E 325: Applied Statistics for Biomedical Engineers
  • ECON 310: Statistics: Measurement in Economics
  • I SY E 210: Introduction to Industrial Statistics
  • STAT 240: Data Science Modeling I
  • STAT 301: Introduction to Statistical Methods
  • STAT 324: Introduction to Statistics for Science and Engineering
  • STAT 371: Introductory Applied Statistics for the Life Sciences
• Statistical Language: 1 credit
  • STAT 303: R for Statistics I
• Regression Analysis (complete one course): 3-4 credits
  • STAT 333: Applied Regression Analysis
  • STAT 340: Data Science Modeling II
• Probability (complete one course): 3 credits
  • E C E 331: Introduction to Random Signal Analysis and Statistics
  • STAT/MATH 309: Introduction to Probability and Mathematical Statistics I
  • STAT 311: Introduction to Theory and Methods of Mathematical Statistics I
  • MATH 331: Introductory Probability
  • STAT/MATH 431: Introduction to the Theory of Probability
  • MATH 531: Probability Theory
• Elective, complete at least 3 credits below: 3 credits
  • STAT 304: R for Statistics II
  • STAT 305: R for Statistics III
  • STAT/MATH 310: Introduction to Probability and Mathematical Statistics II
  • STAT 312: Introduction to Theory and Methods of Mathematical Statistics II
  • STAT 349: Introduction to Time Series
  • STAT 351: Introductory Nonparametric Statistics
  • STAT 405: Data Science Computing Project
  • STAT 411: An Introduction to Sample Survey Theory and Methods
  • STAT 421: Applied Categorical Data Analysis
  • STAT/M E 424: Statistical Experimental Design
  • STAT 433: Data Science with R
  • STAT 436: Statistical Data Visualization
  • STAT 443: Classification and Regression Trees
  • STAT 451: Introduction to Machine Learning and Statistical Pattern Classification
  • STAT 453: Introduction to Deep Learning and Generative Models
  • STAT 456: Applied Multivariate Analysis
  • STAT 461: Financial Statistics
  • STAT/COMP SCI 471: Introduction to Computational Statistics
  • STAT 479: Special Topics in Statistics
  • STAT 575: Statistical Methods for Spatial Data
  • STAT/B M I 620: Statistics in Human Genetics
  • STAT/B M I 641: Statistical Methods for Clinical Trials
  • STAT/B M I 642: Statistical Methods for Epidemiology
• Total Credits: 13

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 students 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 note that they will need at least MATH 211 Survey of Calculus 1/MATH 213 Survey of Calculus 2 or MATH 221 Calculus and Analytic Geometry 1/MATH 222 Calculus and Analytic Geometry 2 to complete the Statistics certificate requirements.