Jan 15, 2025  
2014-2015 Undergraduate Academic Catalog 
    
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2014-2015 Undergraduate Academic Catalog [ARCHIVED CATALOG]

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MA 384 - Statistical Methods for Use in Research

3 lecture hours 0 lab hours 3 credits
Course Description
This course is an introduction to the techniques and methods used in research and seen in published research papers. It assumes a knowledge of the statistical methods generally encountered in an introductory, calculus-based statistics course. Methods such as multiple and nonlinear regression, sequential models regression, two-way analysis of variance, contingency tables, and nonparametric statistical methods from the basis of this course. (prereq: MA 262  or MA 3610  or MA 3620 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Understand the underlying assumptions for the use of any statistical test and understand why those assumptions exist
• Perform single- and multiple-variable regression analyses and be able to provide the correct interpretation of applied hypothesis tests
• Perform and interpret the meaning of a lack-of-fit analysis
• Perform and interpret analyses of categorical data
• Perform and interpret the application of various normality tests
• Perform and interpret stepwise regression techniques
• Correctly assess nonparametric situations, including knowing which nonparametric statistic to apply, which nonparametric hypothesis test to apply, and how to interpret the results obtained using such statistics and performing such hypothesis tests
• correctly determine a statistical test’s power
• correctly determine the sample size necessary for a given statistical situation
Prerequisites by Topic
• Differentiation and partial differentiation
• Integration and multiple integration
• Basic inferential statistical knowledge
• Knowledge of hypothesis testing
Course Topics
• Simple linear regression and correlation (3 classes)
• Multiple and nonlinear regression, including sequential models (5 classes)
• Contingency tables (4 classes)
• Tests of normality (3 classes)
• Two-way analysis of variance (4 classes)
• Nonparametric statistics (8 classes)
• Power and sample size (3 classes)
Coordinator
Ron Jorgensen


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