Course Outline

1. Laying the Foundation & Exploring Data

  • Hypotheses, Theory, & Importance of Measurement
  • Levels of Measurement
  • Visualizing Data
  • Measures of Central Tendency & Dispersion
  • Stata: Summary Statistics
  • The Normal Distribution

2. Inferential Statistics

  • Understanding the Probability in Statistics
  • Sampling & Sampling Bias
  • Sampling Distributions & The Central Limit Theorem
  • Estimator’s Bias & Efficiency
  • Hypothesis Testing with Confidence Intervals & p-values

3. Evaluating Bivariate Relationships

  • ANOVA: Difference of Multiple Means
  • Crosstabs: $\chi^2$
  • Strength of Association
  • Covariance & Correlation
  • Stata: Bivariate Statistics
  • Hurdles of Causality & Regression
  • Turning a Simple Regression into a Multiple Regression
  • Visualizing Regression Results
  • Stata: Regressions

Last updated on Jun 1, 2020

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