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Oct 23, 2026
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PSYC 2280 - Statistics for the Behavioral Sciences Credits: 4
Catalog Description Students use basic mathematical and computerized procedures to analyze data in the behavioral sciences. Use statistical software (e.g., SPSS, “R,” “PSPP”) to conduct descriptive and inferential data analyses. Students choose and apply statistical procedures to help to answer psychological and behavioral scientific research questions. Students read, interpret, and write APA-style results sections for behavioral science research.
Prerequisite(s) (must have a grade of C or better): PSYC 1110 ; MATH 1114 or MATH 1200 or higher Minnesota Transfer Curriculum (MnTC) Goal Area(s) fulfilled: Goal 02: Critical Thinking, Goal 05B: History and the Social and Behavioral Sciences
Additional fee to student: No
Learner Outcomes
- Demonstrate an understanding of the mathematics and logic behind selecting and applying statistical procedures appropriate for a given hypothesis, scale of measurement, and experimental design.
- Perform and describe the statistical procedures commonly used by social scientists including their respective advantages and disadvantages. These include:
- Creating a visual display of data (e.g., bar chart, histogram).
- Measures of central tendency, variability, and frequency distributions.
- Correlational and regression analyses.
- Inferential statistical procedures, including t-tests, ANOVAs, multiple comparison tests, confidence intervals, and effect sizes.
- Nonparametric tests (e.g., chi-square).
- Read, interpret, and summarize basic statistical conclusions from psychological and behavioral science sources accurately and critically evaluate the statistical presentations of others.
- Interpret statistical findings and graphs in the context of their level of statistical significance, confidence intervals, effect sizes, and underlying assumptions, and explain these findings using common language and conventions of the American Psychological Association.
- Use SPSS or another statistical package to build data sets, run univariate analyses, and interpret and display results.
Major Areas of Course Content
- Central tendency and variability
- Basics of inferential statistics: Z scores, the normal curve, sample versus population, and probability
- Hypothesis testing
- Making sense of statistical significance: effect size, confidence intervals, and statistical power
- Choosing appropriate statistics
- Using SPSS or another appropriate statistical package, R, or other statistics program
- Reporting results in APA format
- The t-test: one and two samples (between and within)
- Introduction to analysis of variance
- Factorial analysis of variance
- Correlation
- Regression
- Chi-square tests
Credit for Prior Learning Options No credit for prior learning option is available for this course.
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