Applied Statistics Curriculum

The content of the sequence of stat courses is:

NURS 60N

  1. Major Principles
    1. Randomness & Variables
    2. Samples vs. Populations
      1. Evaluation vs. Research
    3. Descriptive vs. Inferential Statistics
      1. Parametric vs. Non-Parametric Analyses
    4. Related to it is this [online Demonstration
  2. Frequencies & Counts
    1. Frequencies & relative frequencies
    2. Probabilities
      1. Risks & risk ratios
      2. Hazards & hazard ratios
    3. Odds & odds ratios
    4. Contingency / cross tables
      1. Fisher’s exact test
    5. Important distributions
      1. Normal distribution
      2. χ² distribution
  3. Measuring & Testing Differences
    1. Review of Assumptions in Inferential Statistics
    2. Hypothesis Testing
    3. Signal-to-Noise Ratio
    4. Common Tests: t & F
  4. Power and Effect Size
    1. Review & Elaboration of Hypothesis Testing
    2. Power
    3. Effect Size
  5. Association & Causation
    1. Individual Differences and Correlations
    2. Types of Correlation Statistics
    3. Partial and Semipartial Correlations
    4. Concerning Causality
  6. The ANOVA Family of Tests
    1. Basic Concepts of ANOVAs
    2. Main Effects & Interactions
      1. R² & η²
    3. Reading Source Tables
    4. Types of ANOVAs
    5. Family-Wise Error, Post hoc, & Planned Comparisons

NURS 915 & 916

  1. Overview & Review
  2. Handling Data
  3. Presenting Data
  4. Power & Significance
    1. Post hoc power
    2. Sample size estimation
  5. Introduction to Linear Regressions
    1. Method of Ordinary Least Squares
    2. Model Assumptions
  6. Ordinary Least Squares & Maximum Likelihood Estimation
    1. General & Generalized Linear Models
  7. Tests of Model Fit
    1. Information Criteria
    2. Residual Analysis
    3. Stepwise Analysis
    4. Bootstrapping
    5. Missing Values & Outliers
  8. Occurrence, Association, & Causation
    1. Counterfactuals & Hill’s Criteria
    2. Confounds, Mediators, & Moderators
  9. Logistic Regression
    1. Multinomial & Ordinal Logistic Regression
  10. Hierarchical Regression
  11. Longitudinal Analyses
    1. Pre–Post Differences (“Differences in Differences”)
    2. (Repeated-Measures) ANCOVAs with Pretest as Covariate
    3. Multilevel Models of Change
    4. Interrupted Time Series Analysis
  12. Robust Statistics
    1. Bootstrapping
    2. Missing Values & Outliers
  13. Structural Equation Modeling

NURS 925

  1. Foundations of Measurement and Scaling
    1. Psychophysics & Psychometrics
  2. Validity
    1. Traditional, Trinity View
    2. The 1999–2014 Standards & Validity as “Use”
  3. Reliability
    1. Classical Measurement Theory View
    2. As a Measure of a Unitary Construct
    3. As a Measure of Internal Consistency
      1. Cronbach’s α
      2. Kuder-Richardson Formulae 20 & 21
    4. Other Forms (Test-Retest, etc.)
  4. Factor Analysis
    1. Concept and Basic Ideas
    2. Eigenvalues
    3. Exploratory Factor Analysis
      1. Uses and abuses
    4. Confirmatory Factor Analysis
      1. Measures of Model Fit
  5. Return to Structural Equation Modelling