2021-2022 Yavapai College Catalog
 Select a Catalog Preliminary 2024-2025 Yavapai College Catalog 2023-2024 Yavapai College Catalog [PREVIOUS CATALOG YEAR] 2022-2023 Yavapai College Catalog [PREVIOUS CATALOG YEAR] 2021-2022 Yavapai College Catalog [PREVIOUS CATALOG YEAR] 2020-2021 Catalog [PREVIOUS CATALOG YEAR] 2019-20 Catalog [PREVIOUS CATALOG YEAR] 2018-19 Catalog [PREVIOUS CATALOG YEAR]
May 27, 2024
 HELP 2021-2022 Yavapai College Catalog [PREVIOUS CATALOG YEAR] Print-Friendly Page (opens a new window)

# MAT 167 - Elementary Statistics

MAT 1160.
Description: Statistical tools and techniques used in research and general applications. Description of sample data, probability and probability distributions, point and interval estimates of population parameters, hypothesis testing, and correlation and regression. Note: Computer use and graphing calculator required (TI-83/84 recommended).

Prerequisites: MAT 141 , MAT 142 , MAT 152  or satisfactory score on mathematics skills assessment.

General Education Competency: Quantitative Literacy

Credits: 3
Lecture: 3
Course Content:
1. Descriptive statistics
2. Probability
3. Normal distribution
4. Research design
5. Sampling strategies
6. Confidence intervals
7. Hypotheses testing of one population
8. Tests of categorical data
9. Goodness-of-Fit and Contingency Tables
10. Statistics technology

Learning Outcomes:
1. Use both numerical and graphical methods to describe data. (1)
2. Compute and interpret measures of central tendency and variability. (1)
3. Compute probabilities for both simple and compound events. (2)
4. Apply the normal distribution to probability problems and estimation of population parameters. (3)
5. Critique the research methods of others, and use research methodology. (4,5)
6. Produce representative random samples. (5)
7. Calculate and interpret confidence intervals as estimates of population parameters. (6)
8. Perform hypothesis tests about means and other parameters from large and small samples using one and multiple sample methods. (7,8)
9. Test hypothesis about categorical data. (9)
10. Recognize appropriate use of Goodness-of-Fit and Contingency Table tests. (10)
11. Use regression and correlation to test hypothesis and create models for bivariate data. (11)
12. Use technology to perform statistical analysis. (12)