Statistics: Applied Statistics & Analytics

Statistics: Applied Statistics & Analytics

BS

Hours	47 Credit Hours
MAP	Major Academic Plan

Program Requirements

No more than three hours of credit below C- is allowed in major courses.

requirement 1 Complete 1 course

STAT 121 - Principles of Statistics 3.0

requirement 2 Complete 2 courses

Preparation core courses:

MATH 112 - Calculus 1 4.0

MATH 113 - Calculus 2 4.0

requirement 3 Complete 8 courses

Statistics core courses:

STAT 123 - Introduction to R Programming 1.5

STAT 124 - SAS Base Programming Skills 1.5

STAT 223 - Applied R Programming 1.5

STAT 224 - Applied SAS Programming 1.5

STAT 230 - Analysis of Variance 3.0

STAT 240 - Probability and Inference 1 3.0

STAT 330 - Introduction to Regression 3.0

STAT 340 - Probability and Inference 2 3.0

requirement 4 Complete 9.0 hours from the following course(s)

STAT 125 - Introduction to Operating Systems, UNIX, and Shell Programming 1.5

STAT 126 - Introduction to Python Programming 1.5

STAT 226 - SQL 1.5

STAT 234 - Methods of Survey Sampling 3.0

STAT 251 - Introduction to Bayesian Statistics 3.0

STAT 274 - Theory of Interest 3.0

STAT 377 - Statistical Models for Financial Economics 3.0

STAT 381 - Statistical Computing 3.0

STAT 420 - Big Data Science 1 3.0

STAT 421 - Big Data Science 2 3.0

STAT 435 - Nonparametric Statistical Methods 3.0

STAT 437 - Applications in Biostatistics 3.0

STAT 451 - Applied Bayesian Statistics 3.0

STAT 462 - Quality Control and Industrial Statistics 3.0

STAT 466 - Introduction to Reliability 3.0

STAT 469 - Applied Time Series and Forecasting 3.0

STAT 475 - Life Contingencies 3.0

STAT 477 - Statistical Distributions for Actuarial Modeling and Data Analytics 3.0

STAT 495R - Special Topics in Statistics 3.0v

STAT 496R - Academic Internship: Statistics 9.0v

STAT 497R - Introduction to Statistical Research 3.0v

STAT 531 - Experimental Design 3.0

STAT 538 - Survival Analysis 3.0

requirement 5 Complete 9.0 hours from the following course(s)

Note: Courses used above will not double count here.

C S 142 - Introduction to Computer Programming 3.0

IS 515 - Spreadsheets for Business Analysis 3.0

IS 520 - Business Programming and Spreadsheet Automation 3.0

MATH 313 - Elementary Linear Algebra 3.0

MATH 314 - Calculus of Several Variables 3.0

STAT 125 - Introduction to Operating Systems, UNIX, and Shell Programming 1.5

STAT 126 - Introduction to Python Programming 1.5

STAT 226 - SQL 1.5

STAT 234 - Methods of Survey Sampling 3.0

STAT 251 - Introduction to Bayesian Statistics 3.0

STAT 274 - Theory of Interest 3.0

STAT 377 - Statistical Models for Financial Economics 3.0

STAT 381 - Statistical Computing 3.0

STAT 420 - Big Data Science 1 3.0

STAT 421 - Big Data Science 2 3.0

STAT 435 - Nonparametric Statistical Methods 3.0

STAT 437 - Applications in Biostatistics 3.0

STAT 451 - Applied Bayesian Statistics 3.0

STAT 462 - Quality Control and Industrial Statistics 3.0

STAT 466 - Introduction to Reliability 3.0

STAT 469 - Applied Time Series and Forecasting 3.0

STAT 475 - Life Contingencies 3.0

STAT 477 - Statistical Distributions for Actuarial Modeling and Data Analytics 3.0

STAT 495R - Special Topics in Statistics 3.0v

You may take up to 3 credit hours.

STAT 496R - Academic Internship: Statistics 9.0v

You may take up to 3 credit hours.

STAT 497R - Introduction to Statistical Research 3.0v

You may take up to 3 credit hours.

STAT 531 - Experimental Design 3.0

STAT 538 - Survival Analysis 3.0

Program Outcomes:

Fitting Statistical Models

Graduates of the program will demonstrate the ability to analyze data by appropriately fitting, assessing, and interpreting a variety of statistical models

Communication Skills

Graduates of the program will write technical reports and make technical presentations containing statistical results, and work in teams to demonstrate the consulting skills of a professional statistician

Computing Skills

Graduates of the program will be able to manipulate data, implement statistical methods, document, and debug code in one or more profession statistical software programs.

Theoretical Foundations

Graduates of the program will be able to solve problems in basic probability theory, statistical inference, and calculus.

Professional Preparation

Be employable in jobs with BS Statistics requirement