Go to Main Content

Georgetown University

HELP | EXIT

Detailed Course Information

 

Fall 2017
Sep 20, 2017
Transparent Image
Information Select the desired Level or Schedule Type to find available classes for the course.

BIST 511 - Statistical Inference
This course will introduce the basics of statistical inference, parameter estimation, and hypothesis testing in preparation for more in depth coverage of specific models in later courses. Inference procedures: point and interval estimation, sufficient statistics, hypothesis testing, methods of constructing test and estimation procedures. Point estimation: criteria for estimators, maximum likelihood estimators, Bayes estimators, mean square error, unbiased estimators, asymptotic variance of estimators. Hypothesis testing: error probabilities, power function, one-sample inference about the mean with known and unknown variance, comparison of two samples, 2×2 contingency tables, shortcuts and non-parametric methods. Modeling and study design: missing data, extreme observations, transformations, factorial experiments, probability sampling, sample size, two-stage sampling, stratified sampling, nonsampling errors.

3.000 Credit hours
3.000 Lecture hours
0.000 Lab hours

Levels: MN or MC Graduate, Undergraduate
Schedule Types: Lecture

Biostatistics & Epidemiology Department

Restrictions:
Must be enrolled in one of the following Levels:     
      MN or MC Graduate
Must be enrolled in one of the following Majors:     
      Biostatistics
      Biostatistics
      Mathematics and Statistics

Return to Previous New Search
Transparent Image
Skip to top of page
Release: 8.7.2