PSYC 2050 - Statistics for Psychology

Credits: 4
Hours/Week: Lecture 4 Lab None
Course Description: This course is designed for individuals interested in learning the fundamentals of statistical analysis and research design in psychology. Course activities will cover the analysis of psychological research data using both descriptive and inferential statistics. Data analysis will be performed manually and with statistical software packages such as SPSS, Jamovi, or R. Key topics include the selection and application of appropriate statistical procedures to investigate psychological and behavioral research questions. Other coursework will involve reading, interpreting, and writing APA-style “Results” sections for behavioral science research.
MnTC Goals
None

Prerequisite(s): MATH 1025 (preferred) or MATH 1061 or above with a grade of C or higher and PSYC 1020 with a grade of C or higher.
Corequisite(s): None
Recommendation: None

Major Content

Basics of Inferential Statistics:
- The normal curve
- Z scores
- Sample versus population
- Probability
- Dependent and independent variables
Central Tendency and Variability
- Mean, median, and mode
- Range, variance, standard deviation
Hypothesis Testing
- Null hypothesis
- Alternative hypothesis
- Type I and Type II Errors
Making Sense of Statistical Significance:
- Confidence intervals
- Effect size
- Statistical power
Choosing Appropriate Statistics
- Chi-square Tests
- Correlation
- Regression Analysis
- The t-test
- Analysis of Variance (ANOVA)
Using SPSS or Other Appropriate Statistical Package (e.g., R, SAS, Excel, Stata)
- Creating data sets

Learning Outcomes

At the end of this course, students will be able to:

explain basic statistical vocabulary and concepts and the role of statistics in the scientific method.
create frequency distributions and visual displays of data appropriate for specific types of data.
calculate measures of central tendency and variability.
perform correlational and regression analyses.
apply appropriate inferential statistical procedures for a given hypothesis, scale of measurement, and experimental design, including t-tests, ANOVA, and post-hoc tests.
perform nonparametric tests, including chi-square and the Mann-Whitney U test.
compare the advantages and disadvantages of various statistical procedures.
explain and interpret statistical results considering their level of statistical significance, confidence intervals, effect sizes, and underlying assumptions using common language and American Psychological Association (APA) conventions.
evaluate basic statistical conclusions from psychological and behavioral science sources and the statistical presentations of others.
use SPSS or other statistical packages (e.g., Jamovi, R, SAS, Excel) to build data sets, run univariate analyses, and interpret and display results according to APA guidelines.

Minnesota Transfer Curriculum (MnTC): Goals and Competencies
Competency Goals (MnTC Goals 1-6)
None
Theme Goals (MnTC Goals 7-10)
None

Courses and Registration