Intermediate Statistics for Economics

Course Syllabus

• Statistics vs. Parameters: fundamental distinction
• Distribution Theory: sampling distributions and their mathematical foundations
• Central Limit Theorem: normal approximations for large-scale economic data analysis
• Point Estimation: Method of Moments and Method of Maximum Likelihood
• Properties of Estimators: Consistency, Unbiasedness, and Efficiency
• Interval Estimation: constructing confidence intervals and determining sample size
• Statistical Hypothesis: meaning and structure
• Error Analysis: identifying and mitigating Type 1 and Type 2 errors
• Power of a Test: ensuring reliability of empirical findings
• Tests for population means and proportions — small and large samples
• P-value approach for modern significance testing
• Two-sample tests for equality of means and ratios of variances

Reference Books

• Devore, J. (2012). Probability and Statistics for Engineers, 8th ed. Cengage Learning.
• Rice, J. A. (2007). Mathematical Statistics and Data Analysis, 3rd ed. Thomson Brooks/Cole.
• Larsen, R., Marx, M. (2011). Mathematical Statistics and Its Applications. Prentice Hall.
• Miller, I., Miller, M. (2017). J. Freund's Mathematical Statistics with Applications, 8th ed. Pearson.
• Hogg, R., Tanis, E., Zimmerman, D. (2021). Probability and Statistical Inference, 10th ed. Pearson.

Who Will Teach You