May 06, 2024  
2017-2018 Undergraduate Bulletin 
    
  Bulletin Home
  Course Descriptions
  Academic Programs/Majors
  General Education, RES, GLP
  Glossary of Academic Terms
  Archived Bulletins
  The University
  Admission
  Scholastic Standards
  Tuition and Fees
  Financial Assistance
  Services for Students
  Teacher Education
  My Favorites
HELP
2017-2018 Undergraduate Bulletin [ARCHIVED]

Course Descriptions

A typical course description in the Undergraduate Bulletin appears like this:

LIT 273 American Multicultural Literature  

The three digits of the course codes refer to the course level. Undergraduate courses are those numbered from 100 to 499. All numbers above that are for graduate credit.The 100 series is primarily for freshmen; 200 – sophomores; 300 – juniors; and 400 – seniors.

Course Planning Information

Information included with the course description helps you as you plan your course schedules. General Education (Gen Ed), Racial and Ethnic Studies (RES), Global Perspective (GLP), repeatability, and terms offered (if known) are indicated.

The terms indicated serve only as a general guide and do not guarantee that a course will be offered during a particular semester. Verify availability of a course in any given term by checking the online Open Courses listing or through Access Stout when planning your schedule.
 

Statistics
  

  • STAT-130 Elementary Statistics

    (2 cr.)
    Analytical Reasoning and Natural Sciences - Analytic Reasoning
    Repeatable for Credit: No
    Concepts and application of probability and statistics: data analysis (graphical displays, numerical summary measures); probability and probability distributions; concepts of statistical inference (estimation and hypothesis testing). Illustrated with output from statistical computing packages. Students may incur incidental expenses for software.
  

  • STAT-320 Statistical Methods

    (3 cr.)
    Analytical Reasoning and Natural Sciences - Analytic Reasoning
    Repeatable for Credit: No
    Methods of describing data: graphical methods, numerical summary measures, exploratory data analysis. Probability, probability distributions, expected value. Sampling distributions. Statistical inference: estimation and hypothesis testing for one-sample and two-sample problems. Regression analysis. Demonstrating with standard statistical software packages. Students may incur incidental expenses for software.
    Prerequisite: Math Placement or MATH-120  
  

  • STAT-330 Probability and Statistics for Engineering and the Sciences

    (3 cr.)
    Repeatable for Credit: No
    Exploratory data analysis; basic probability, probability distributions, mathematical expectation, sampling distributions; basic statistical inference (estimation and hypothesis testing); topics in reliability.
    Prerequisite: take MATH-154  or MATH-157  
  

  • STAT-331 Probability and Mathematical Statistics I

    (3 cr.)
    Repeatable for Credit: No
    Sample spaces. Probability functions for discrete and continuous sample spaces. Conditional probability and independence. Random variables; probability density and cumulative distribution functions; joint, marginal, and conditional distributions. Expected values, moments, and moment-generating functions. Binomial, hypergeometric, Poisson, normal, and gamma distributions.
    Prerequisites: take MATH-154  or MATH-157 . Prerequisite or concurrent enrollment in MATH-158  
  

  • STAT-332 Probability and Mathematical Statistics II

    (3 cr.)
    Repeatable for Credit: No
    Point estimation. Properties of point estimators: unbiasedness, efficiency, consistency, sufficiency. The method of maximum likelihood. Basic concepts of interval estimation and hypothesis testing. Inference in one-sample and two-sample problems. Simple linear regression analysis; the method of least squares. Goodness-off-it tests. Analysis of categorical data.
    Prerequisite: take STAT-331  
  

  • STAT-440 Advanced Linear Modeling-Regression and Time Series Analysis

    (3 cr.)
    Repeatable for Credit: No
    Multiple regression, inference about regression parameters, remedical regression measures, quantitative and qualitative regression, model selection/validation, nonlinear regression, neural networks, logistic and Poisson regression, generalized linear models, time series, smoothing, stochastic time series, moving average and autoregressive models, auto regressive integrated moving average (ARIMA), estimating and forecasting with time series.
    Prerequisite: take STAT-332  
  

  • STAT-499 Independent Study

    (1-3 cr.)
    Repeatable for Credit: Yes
    Department Consent