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# 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.
Gen-Ed: Meets AGEC - MATH; Meets CTE - M&S.

Course Learning Outcomes
1. Compute simple and conditional probabilities.
2. Display, analyze, and model quantitative and categorical random variables.
3. Determine confidence intervals for population means and proportions.
4. Test claims for population means and proportions using hypothesis testing.

Performance Objectives:
1. Define the nature of statistics.
2. Display quantitative data using a variety of tables and graphs and compute measures of central tendency, variability, and position.
3. Compute simple and conditional probabilities, and determine independence of events.
4. Define a random variable and compute its distribution, mean, and variance.
5. Describe the following probability distributions and their uses: binomial, standard normal, normal, student’s t, and chi-square.
6. State and apply the central limit theorem.
7. Determine point estimations and confidence intervals for one population mean and proportion.
8. Test claims for population mean and proportion using hypothesis testing and examine Type I and Type II errors.
9. Determine confidence intervals and test claims using hypothesis testing for two population means and proportions and examine independent samples and paired samples.
10. Determine a regression line and compute the corresponding correlation coefficient and test to determine significance.
11. Choose at least one of the additional topics: hypothesis testing for variance, hypothesis testing for goodness of fit, test for independence using the chi-square distribution, test for homogeneity of proportions, ANOVA, or nonparametric methods.

Outline:
1. Nature of Statistics
1. Descriptive and inferential statistics
2. Data type
3. Design of experiments
4. Population versus sample
1. Quantitative Data
1. Tables
2. Graphs
3. Measures of central tendency
1. Mean
2. Mode
3. Standard deviation
1. Probability
1. Discrete simple
2. Discrete conditional
3. Determine independence of events
4. Random variable distributions
2. Probability Distributions
1. Binomial
2. Normal
3. Student’s t
4. Chi-square
3. Central Limit Theorem
4. Estimates for Population Statistics
1. Point
2. Intervals
5. Hypothesis Testing
1. One population tests
2. Two population tests
6. Correlation and Regression