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Program

Updated A.Y. 2019-2020

Chapter Title
Introduction to a course
What will we learn on this course
Chapter 1 ECONOMIC QUESTIONS AND DATA
Economic questions we examine
Causal effects and idealized experiments
Data: Sources and types
Chapter 2 REVIEW OF PROBABILITY
Random variables and probability distributions
Expected values, meand and variance
Two random variables
Normal, Chi-squared, t-distribution, F-distribution
Properties of estimators
Law on large numbers and Central limit theorem
XXXXXXX INTRODUCTION TO GRETL
Chapter 3 REVIEW OF STATISTICS
(skipped)
Chapter 4 LINEAR REGRESSION WITH ONE REGRESSORS
The linear regression model
Estimating the coefficients of the linear regression model
Measures of fit
The least squares assumptions
Sampling distributions of OLS estimators
Chapter 5 REGRESSION WITH A SINGLE REGRESSOR: HYPOTHESIS TESTING AND CONFIDENCE INTERVALS
Testing hypotheses about one of the regression coefficients
Confidence intervals for a regression coefficients
Regression when X is a binary variable
Heteroscedasticity and homoskedasticity
The theoretical foundations of ordinary least squares
Using the t-statistic in the regression when the sample size is small
Chapter 6 LINEAR REGRESSION WITH MULTIPLE REGRESSORS
Omitted variable bias
The multiple regression model
The OLS estimator in multiple regression
Measures of fit in multiple regression
The least squares assumptions in multiple regression
The distribution of the OLS estimators in multiple regression
Multicollinearity
Chapter 7 HYPOTHESIS TESTS AND CONFIDENCE INTERVALS IN MULTIPLE REGRESSION
Hypothesis tests and confidence intervals for a single coefficient
Tests of joint hypotheses
Testing single restrictions involving multiple coefficients
Confidence sets for multiple coefficients
Model specification for multiple regression
Analysis of the test score data set
Chapter 8 NONLINEAR REGRESSION FUNCTIONS
A general strategy for modeling nonlinear regression functions
Nonlinear functions of a single independent variable
Interactions between independent variables
Nonlinear effects on test scores of the student-teacher ratio
Chapter 9 ASSESSING STUDIES  BASED ON MULTIPLE REGRESSION
Internal and external validity
Threats to internal validity of multiple regression analysis
Internal and external valitidy when the regression is used for forecasting
Example: Test scores and class size