# [Play Econometrics with R] Preview for Chapter 1-2 released!

I'm glad to announce that now the preview version for my brochure Play Economics with R has been released! This time I publish the first two chapters, which were just finished several days ago. At present it is written in Chinese, so there is only an English content for none-Chinese readers.

## Content

### Chapter 1 Get familiar with R

1.1 Data Import...................................... 6
1.2 Summary the data....................................... 7
1.2.1 Average value..................................... 7
1.2.2 Linear regression (ordinary least squares, OLS).................... 8
1.3 Plot a regreesion figure...................................... 9
1.4 Point prediction......................................... 10
1.5 Multiple linear regression..................................... 10
1.6 Save and edit the code.................................... 11
1.7 Search for help....................................... 11

### Chapter 2 Start from cross-section data

2.1 Parameter test....................................... 12
2.1.1 t test..................................... 13
2.1.2 F test..................................... 13
2.2 Confidence Intervals....................................... 14
2.3 Dummy variables....................................... 14
2.3.1 grouped by the nature.................................. 14
2.3.2 grouped by the value................................. 14
2.3.3 interaction items................................... 15
2.3.4 specify the based group.................................. 17
2.4 Heteroscedasticity test...................................... 18
2.4.1 BP test (Breusch-Pagan Test)........................ 19
2.4.2 White test (White test for heteroskedasticity)................ 20
2.5 Robust standard deviation...................................... 20
2.6 Weighted least squares estimation (WLS).............................. 21
2.6.1 with disturbance form known ............................... 21
2.6.2 feasible generalized least squares (Feasible GLS, FGLS)................ 22
2.7 Generalized Linear Estimation (GLM)................................. 24
2.7.1 Maximum Likelihood Estimation (MLE).......... 25
2.7.2 Probit and Logit models.............................. 25
2.7.3 Tobit model................................... 26
2.7.4 Ordered Logit / Probit............. 27
2.8 Count Model............................... 28
2.8.1 Poisson Regression Model................... 28
2.8.2 test for dispersion.............................. 29
2.8.3 Negative binomial regression model............. 30
2.8.4 Zero-inflated Poisson model (ZIP)............ 30
2.9 Sample Selection Bias.................................... 32
2.9.1 Heckit model.................................. 32
2.10 Simultaneous Equations Model..................................... 33
2.10.1 two-stage least squares (2SLS) and instrument variable................... 33
2.10.2 Simultaneous Equations Model Estimation: Seemingly Unrelated Regression (SUR)... 34
2.11 Proxy Variables....... 35