ECN 102A Syllabus PDF

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ECN 102A Syllabus and Lecture Outline...

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ECN 102A:! ANALYSIS OF ECONOMICS DATA ! SYLLABUS (Revised June 1) Department of Economics, University of California - Davis SPRING 2020 A. Introduction: Lecture 1: Introduction and getting going on Stata! (chapter 1 + Stata http://cameron.econ.ucdavis.edu/stata/stata.html). B. Univariate: Analysis of a single economics variable Lecture! 2-3: Summarizing data using descriptive statistics and visualizing data using charts (chapter 2.1-2.4, 4.3.1) Lecture! 4: The sample mean (chapter 5.1-5.4, 5.7-5.8) Lecture! 5-6: Begin statistical inference: properties of estimator of sample mean (chapter 5.5-5.6) Lecture! 7: Confidence intervals based on the sample mean (chapter 6.1-6.3) Lecture! 8: Statistical inference based on the sample mean using t tests (chapter 6.4, 6.6) Lecture! 9: ***** Midterm exam zero! (covers lectures 1-7) ***** C. Bivariate: The relationship between two economic variables Lecture 10: Statistical inference based on the sample mean using t tests (chapter 6.4, 6.6) Lecture 11: Extensions of hypothesis tests (chapter 7.1-7.3) Lecture 12: ***** Midterm exam one: covers univariate statistics) ***** Lecture 13-14: Bivariate data summary: scatter plots, correlation and regression (chapter 8.1-8.10) Lecture 15-16: The least squares estimates (chapter 9.1-9.5) Lecture 17-18: Statistical inference on regression coefficients (chapter 9.4, 10.1-10.9) !!!!!!!!!!!!!!!!!!!!!!!! and Bivariate case studies (chapter 11.3) Lecture 19: Natural logarithms (slides: traedv1_09_update_natural_logarithms.pdf)

Lecture 20: Mostly review Lecture 21: ***** Midterm exam two (covers bivariate regression) ***** D. Multiple regression: The relationship between more than two economic variables Lecture 22: Multiple regression (chapter 13.1-13.8) Lecture 23-24: Inference for multiple regression (chapter 14.1-14.9) !!!!!!!!!!!!!!!!!!!!!!!! and Case study (chapter 15.1) Lecture 25-26: Regression with indicator variables (chapter 12.2, 16.4-16.6) Lecture 27: Regression with nonlinear models (quadratic, natural logarithm) (chapter 12.3, 16.4-16.6) Lecture 28: Review...