PSYC-FPX3700 builds statistical competency specifically for psychology, covering the statistical tests and concepts most commonly encountered in published psychological research.
Statistical concepts foundational to psychological research
PSYC-FPX3700 covers descriptive and inferential statistics as they're specifically applied within psychological research, building the literacy needed to read published studies critically.
Interpreting statistical significance and effect size
The course covers correctly interpreting statistical significance and effect size, addressing common misinterpretations of what a statistically significant finding actually means.
Key topics in PSYC-FPX3700
- Descriptive and inferential statistics for psychology
- Correctly interpreting statistical significance
- Understanding and interpreting effect size
- Common statistical tests in psychological research
- Reading and critically evaluating a research study's statistics section
- Avoiding common statistical misinterpretations
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Worked example: statistical significance versus practical importance
- Common misinterpretation: Assuming a statistically significant finding automatically means the effect is large or practically important
- Accurate interpretation: Statistical significance indicates a finding is unlikely due to chance, but says nothing about the actual size or practical importance of the effect — that's what effect size measures separately
- Lesson: A statistically significant finding with a very small effect size may have limited practical importance, despite being 'significant' in the statistical sense
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Frequently asked questions
Statistical significance specifically indicates that an observed result is unlikely to have occurred purely by chance, but it says nothing directly about how large or practically meaningful the actual effect is — with a large enough sample size, even a very small, practically negligible effect can reach statistical significance, while a genuinely large, practically important effect might not reach significance with a small sample. PSYC-FPX3700 teaches the distinction between statistical significance and effect size because conflating the two is one of the most common statistical misinterpretations in reading psychological research, and genuinely critical research evaluation requires considering both dimensions together, not treating statistical significance alone as confirmation of practical importance.
While core statistical principles are shared across disciplines, psychological research involves specific methodological considerations, common study designs, and particular statistical tests that appear especially frequently in psychological literature, and dedicated training that presents these concepts specifically within a psychological research context helps students more directly connect abstract statistical concepts to how they're actually applied and reported in the studies they'll read and eventually conduct within their own field. PSYC-FPX3700 provides this psychology-specific statistical training because building this direct connection between statistical concept and actual psychological research application produces more genuinely useful competency than general statistics training disconnected from psychology's specific research context.