Psychological Statistics (PIA-137)

Semester:
Fall 2025
Course Number:
0501-137-007
Instructor:
Caitlin Lapine
Days:
Tuesday Thursday 9:25 am - 10:40 am
Format:
Traditional in-person class
Location:
Garden City - Nexus Building
Credits:
4
Notes:

Student must register for lecture and lab
Must register for correspondong lab 0501-137-710

Course Materials:
Description:

This course is designed to give a general understanding of how statistics can be used to help answer questions in psychological research. The course presents descriptive and inferential statistics and their applications. The laboratory component of this course will give you an opportunity to develop skills in using statistical software. (Learning Goals:Q;Distribution Reqs:Mathematics,Computing & Logic)

Learning Goals:

(1) Understand basic concepts of psychological statistics and how it is used to answer questions in psychological research. (2) Summarize numeric data by computing descriptive statistics (e.g., mean, variance) and by creating tables and graphs.(3) Compute various inferential statistics (e.g., t-score). (4) Test hypotheses applying probability theory.(5) Explain the differences among various statistical techniques and identify an appropriate technique for a given set of variables and research questions.(6) Interpret basic statistical results and distinguish between statistical significance and practical significance.(7) Evaluate the validity of conclusions presented in research reports and in the media.(8) Understand and utilize a statistical software package (SPSS for Windows) and Excel for Windows for data organization, display and computation of statistical procedures discussed in the lecture.

*The learning goals displayed here are those for one section of this course as offered in a recent semester, and are provided for the purpose of information only. The exact learning goals for each course section in a specific semester will be stated on the syllabus distributed at the start of the semester, and may differ in wording and emphasis from those shown here.

Prerequisites:

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