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PSY 60000 Statistical Inference

3 credits

  • Prerequisites: None
  • Delivery: On-Campus
  • This course introduces the foundations of inferential statistics, both parametric and nonparametric, including probability theory. Students study the general linear model, statistical analyses for inferences about mean differences (e.g., t-tests, ANOVA) and strengths of relation (e.g., correlation, regression), and their application to research.

    Learning Outcomes

    1. Display, interpret, and explore data using descriptive statistics and graphs.
    2. Explore assumptions about the data, including normality, skew, and kurtosis.
    3. Use random variables and probability distributions.
    4. Determine whether and how to perform statistical inference.
    5. Perform parametric (e.g., t-test, ANOVA, ANCOVA, MANOVA) and nonparametric (e.g., chi-square) hypothesis testing and correlation.
    6. Fit linear regression models and interpret their parameters.