The Curriculum

The content of the sequence of stat courses is:

NURS 60N

  1. Fundamental Concepts
    1. Randomness & Variables
    2. Descriptive vs. Inferential Statistics
    3. Samples vs. Populations
      1. Standard Error of the Mean & Regression to the Mean
      2. Central Limit Theorem
    4. Evaluation vs. Research
    5. Parametric vs. Non-Parametric Analyses
  2. Descriptive Statistics
    1. Steven’s Levels of Measurement
    2. Central Tendency & Dispersion
  3. Frequency, Probability, & Odds
    1. Probabilities, Risks, & Hazards
    2. Odds
    3. Contingency Tables
      1. Fisher’s Exact Test
  4. Introduction to Distributions
    1. Normal Distribution
    2. χ² Distribution
  5. Applications of Distributions
    1. Confidence Intervals
    2. Standardization
      1. z Scores
  6. Variance & Covariance
    1. Correlations & Partial Correlations
    2. Signal-to-Noise Ratio
  7. Hypothesis Testing
    1. Null Hypothesis
    2. Power & Effect Size
      1. Sample Size Estimation
  8. t Tests
    1. Paired t test
    2. Two-Sample t Test (Equal & Unequal Samples)
  9. Introduction to Linear Regressions
    1. Method of Ordinary Least Squares
    2. Model Assumptions
  10. Introduction to ANOVAs
    1. Main Effects & Interactions
    2. Reading Source Tables
    3. R² & η²
    4. Family-Wise Error, Post hoc, & Planned Comparisons
  11. The ANOVA “Family” of Models: ANCOVAs, MANOVAs, & repeated-Measures ANOVAs

NURS 915 & 916

  1. Handling Data
  2. Presenting Data
  3. Linear Relationships
  4. Occurrence, Association, & Causation
    1. Counterfactuals & Hill’s Criteria
    2. Confounds, Mediators, & Moderators
  5. Ordinary Least Squares & Maximum Likelihood Estimation
    1. General & Generalized Linear Models
  6. Tests of Model Fit
    1. Information Criteria
    2. Residual Analysis
    3. Stepwise Analysis
    4. Bootstrapping
    5. Missing Values & Outliers
  7. Logistic Regression
    1. Multinomial & Ordinal Logistic Regression
  8. Hierarchical Regression
  9. 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
  10. 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