STANDARD

MAT 198 – INTRODUCTION TO STATISTICS

Course Description

Discusses the concepts and methods fundamental to utilizing and interpreting commonly used statistics. Topics include: descriptive statistics, basic probability, discrete and continuous distributions, sampling distributions, hypothesis testing, chi square tests, and linear regression.

Competency Areas Hours

Descriptive Statistics Basic Probability Discrete and Continuous Distributions Sampling Distributions Hypothesis Testing Chi Square Tests Linear Regression

Class/Week D.Lab/Week P.Lab/Week Credit Hours

5 0 0 5

Prerequisite: Program admission level math achievement

COURSE GUIDE

Competency	After completing this section, the student will:	Hours
		Class	D.Lab	P.Lab
DESCRIPTIVE STATISTICS		3	0	0
Data display Data manipulation	Draw stem-leaf diagrams and histograms. Compute mean, median, mode, and standard deviation.
BASIC PROBABILITY		7	0	0
Events Probability rules	Define events, compound events, and complementary events. Compute probabilities for unions, intersections, and complements. Compute conditional probabilities.
DISCRETE AND CONTINUOUS DISTRIBUTIONS		10	0	0
Random variables Discrete random variables Continuous random variables	Demonstrate an understanding of the difference between discrete and continuous random variables. Use probability distributions to compute expected value of a discrete random variable. Compute probabilities for binomially distributed random variables. Compute expected value and variance of a binomially distributed random variable. Compute probabilities for normally distributed random variables. Use the normal distribution to estimate probabilities for binomially distributed random variables.
SAMPLING DISTRIBUTIONS		10	0	0
Central limit theorem Sample size Confidence intervals	Use the normal distribution to compute probabilities for samples. Determine the sample size required to meet certain requirements for the standard deviation. Determine large-sample and small-sample confidence intervals for population means.
HYPOTHESIS TESTING		10	0	0
Definitions Large sample test on population mean Small sample test on population mean	Explain the meaning of the null and alternative hypothesis. Define the meaning of a Type I (a) error. Define the meaning of a Type II (b) error. Test a hypothesis about a population mean using a large sample (normal distribution). Test a hypothesis about a population mean using a small sample (student’s t distribution).
CHI SQUARE TESTS		5	0	0
Hypothesis test Goodness of fit	Compare two or more population proportions and test for differences in populations. Test how well the binomial or normal distribution fits a data set.
LINEAR REGRESSION		5	0	0
Linear function to variable quantities Correlation coefficient to random variables	Fit a linear function to best represent the relationship between two variable quantities. Compute and evaluate the correlation coefficient to measure the relationship between two random variables.

Suggested Resources

Suggested Resources include textbooks shown below or most current edition.

Devore, J., & Peck, R. (1990). Introductory statistics. St. Paul: West.

Ingram, J. A., & Monks, J. G. (1989). Statistics for business and economics. Orlando,

FL: Harcourt Brace Jovanovich.

McClave, J. T., & Dietrich, F. H. (1989). A first course in statistics (3rd ed.). Riverside,

NJ: Dellen.