
20232024 College Catalog [ARCHIVED CATALOG]

MAT 167  Introductory Statistics [SUN# MAT 1160] 3 Credits, 3 Contact Hours 3 lecture periods 0 lab periods
Introduction to statistics. Includes the nature of statistics, quantitative data, probability, probability distributions and the central limit theorem. Also includes estimates for population parameters, hypothesis testing, correlation with regression, and additional topics with choices from chi square distribution, ANOVA and/or nonparametric methods.
Prerequisite(s): Within the last three years: MAT 151 with a grade of C or better, or required score on the Mathematics assessment test. Information: Use of a graphing calculator and/or computer programs may be required at the discretion of the instructor. Access to a scanner required for math classes taken online. GenEd: Meets AGEC  MATH; Meets CTE  M&S.
Course Learning Outcomes
 Compute simple and conditional probabilities.
 Display, analyze, and model quantitative and categorical random variables.
 Determine confidence intervals for population means and proportions.
 Test claims for population means and proportions using hypothesis testing.
Performance Objectives:
 Define the nature of statistics.
 Display quantitative data using a variety of tables and graphs and compute measures of central tendency, variability, and position.
 Compute simple and conditional probabilities, and determine independence of events.
 Define a random variable and compute its distribution, mean, and variance.
 Describe the following probability distributions and their uses: binomial, standard normal, normal, student’s t, and chisquare.
 State and apply the central limit theorem.
 Determine point estimations and confidence intervals for one population mean and proportion.
 Test claims for population mean and proportion using hypothesis testing and examine Type I and Type II errors.
 Determine confidence intervals and test claims using hypothesis testing for two population means and proportions and examine independent samples and paired samples.
 Determine a regression line and compute the corresponding correlation coefficient and test to determine significance.
 Choose at least one of the additional topics: hypothesis testing for variance, hypothesis testing for goodness of fit, test for independence using the chisquare distribution, test for homogeneity of proportions, ANOVA, or nonparametric methods.
Outline:
 Nature of Statistics
 Descriptive and inferential statistics
 Data type
 Design of experiments
 Population versus sample
 Quantitative Data
 Tables
 Graphs
 Measures of central tendency
 Mean
 Mode
 Standard deviation
 Probability
 Discrete simple
 Discrete conditional
 Determine independence of events
 Random variable distributions
 Probability Distributions
 Binomial
 Normal
 Student’s t
 Chisquare
 Central Limit Theorem
 Estimates for Population Statistics
 Point
 Intervals
 Hypothesis Testing
 One population tests
 Two population tests
 Correlation and Regression
 Additional Topics
 Chisquare distribution hypothesis testing
 Test for variance
 Test for goodness of fit
 Test for independence
 Test for homogeneity of proportions
 ANOVA
 Nonparametric methods
Effective Term: Fall 2015

