Course Homepage: (Past pages: Fall 2003 - Section 2)

Usually Offered: Fall, Spring, and Summer Semesters

Purpose: To familiarize students in a variety of fields with modern statistical methods, including the general areas of data description, elementary probability, and inference from data, presenting applications in many areas such as health, social, and physical sciences, education, and business. To prepare the students to further their study in statistical topics such as quality control, design of experiments, nonparametrics, times series, and sampling.

Current Textbook: Statistics, 10/E, by J.T. McClave and T. Sincich, Prentice Hall, 2003.

Supplementary Material: Eight supplements to the textbook are available for download in .pdf format:

    Annotations to the Text
    Chapter 6 - More on Sampling Distributions: t, chi-square and F
    Chapter 7 - Confidence Intervals for Variances
    Section 8.6 - Power Curves
    Section 10.2 - The ANOVA Table
    Section 11.3 - Checking the Regression Assumptions
    Section 11.5 - The ANOVA Table for Regression
    Section 13.3 - Chi-Square Test for Homogeneity

Help in using SAS can be found on the SAS Templates page. This page is designed to be used interactively and is probably too long to print out.

Topics Covered	Chapters	Time
Descriptive Statistics: graphical methods, measures of center and variability, use of SAS	1-2, S	2 weeks
Basic Probability: basic rules of probability, probability distributions, binomial random variable and counting rules, normal distribution, normal approximation of the binomial (special case of the central limit theorem)	3-5	2.5 weeks
Sampling Distributions: central limit theorem; t, chi-squared, and F distributions	6, S	1 week
Estimation and Inference: confidence intervals and hypothesis tests for one and two means, variances, and proportions; p-value; power	7-9, S	3.5 weeks
One-way ANOVA: the analysis of variance table and partitioning the sum of squares	10.1-2, S	1 week
Simple Linear Regression: the least squares regression line, hypothesis testing and prediction, checking assumptions, the correlation coefficient	11, S	2.5 weeks
Categorical Data Analysis: tests for independence, homogeneity, and goodness of fit	13, S	1 week

 

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: David Hitchcock, Brian Habing
(Last Updated: July 11, 2008)