Course Description
Basic statistical analysis for students in quantitative disciplines other than statistics. Topics include principles of sampling and descriptive statistics, elementary probability and probability distributions, discrete and continuous random variables, normal distribution, sampling distributions, statistical inference for one and two samples, simple linear regression, basic nonparametrics, and chi-squared tests.
Athena Title
Statistical Analysis I
Equivalent Courses
Not open to students with credit in STAT 6210, STAT 6210E, STAT 6315, STAT 6315E
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
This is a first course in statistics for quantitatively oriented students from disciplines other than statistics. It is suitable for students who intend to take two or more courses in statistical methodology and/or put statistical techniques into practice to analyze real data. Upon completion of the course, students will understand the paradigm of statistical inference about a population through statistical analysis of sample data. They will learn how to compute and interpret basic descriptive statistics such as means, medians, and standard deviations. They will understand basic probability and how to apply it, and will know the definition, interpretation, and use of probability distributions including the normal and binomial distributions. Students will be trained in methods of inference about means and proportions based upon one and two sample data and their implementation in the statistical software package SAS. Time permitting, students will receive an introduction to simple linear regression, nonparametric statistical methods, and chi-square tests for two-way tables.
Topical Outline
Core topics include principles of sampling; descriptive statistics including measures of location and dispersion, elementary probability and probability distributions, discrete and continuous random variables, normal distribution, sampling distributions of basic statistics, one and two sample confidence intervals and hypothesis tests for means and proportions. Implementation of basic statistical methods in SAS. Additional topics that may be introduced are simple linear regression, correlation, basic nonparametric statistical methods, and statistical inference for two-way contingency tables.
Syllabus