

Course ID:  STAT 6310. 3 hours. 
Course Title:  Statistical Analysis I 
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 chisquared tests. 
Oasis Title:  Statistical Analysis I 
Duplicate Credit:  Not open to students with credit in STAT 6210, STAT 6315 
Semester Course Offered:  Not offered on a regular basis. 
Grading System:  AF (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
chisquare tests for twoway 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 twoway contingency
tables. 