Publications by Rui Fan
Lab 7: Inference for Multiple Regression Models
In this lab exercise, you will learn: No Perfect Multicollinearity Assumption To check imperfect multicollineartiy, find the sample correlation matrix for all independent variables using cor. Statistical Inference for Multiple Regressions linearHypothesis in package car. Heteroskedasticity robust SE: vcovHC Confidence interval using robust SE: ...
7328 sym R (12575 sym/36 pcs)
Lab 6: Assignment Solutions
E6.1 Use the Birthweight_Smoking data set introduced in Empirical Exercise E5.3 to answer the following questions. Start the project by clearing the workspace. Then load the R package openxlsx and the data Birthweight. rm(list=ls()) library(openxlsx) id <- "1IL42szr5_GLat_hqY30yJVV_JVHxHEmO" bw <- read.xlsx(sprintf("https://docs.google.com/uc?id=%...
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Lab 6: Multiple Regression
In this lab exercise, you will learn: Multiple Regression Using R \(lm(y \sim x_1+x_2+x_3)\) How to interpret results of multiple regressions. \(SER\), \(R^2\), and \(\bar R^2\). Exercise: The Gender Wage Gap The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are working. Women are gene...
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Lab 5: Assignment Solutions
E5.1 Use the data set Earnings_and_Height described in Empirical Exercise 4.2 to carry out the following exercises. Start the project by clearing the workspace. Then load the R package openxlsx and the data Earnings_and_Height. rm(list=ls()) library(openxlsx) id <- "1XKjDOQBJcxwslhwipkJAF2qLNmFW9Bfu" earn <- read.xlsx(sprintf("https://docs.google....
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Lab 5: Inference for Simple Linear Regression with 1 Regressor (with solutions)
In this lab exercise, you will learn: Regression with dummy variables How to interpret coefficients How to construct confidence intervals and conduct hypothesis tests Heteroskedasticity Visual inspection for heteroskedasticity How to obtain robust standard errors (SE): vcovHC How to conduct significance test using robust SE: coeftest Exercise ...
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Lab 5: Inference for Simple Linear Regression with 1 Regressor
In this lab exercise, you will learn: Regression with dummy variables How to interpret coefficients How to construct confidence intervals and conduct hypothesis tests Heteroskedasticity Visual inspection for heteroskedasticity How to obtain robust standard errors (SE): vcovHC How to conduct significance test using robust SE: coeftest Exercise ...
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Lab 4: Assignment Solutions
Start the project by clearing the workspace. Then load the R package openxlsx and the data Earnings_and_Height. rm(list=ls()) library(openxlsx) id <- "1XKjDOQBJcxwslhwipkJAF2qLNmFW9Bfu" earn <- read.xlsx(sprintf("https://docs.google.com/uc?id=%s&export=download",id),sheet=1,startRow=1,colNames=TRUE,rowNames=FALSE) str(earn) ## 'data.frame': 178...
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Lab 4: Simple Linear Regression with 1 Regressor (with solutions)
In this lab exercise, you will learn: How to make a scatter plot plot How to run an OLS regression in R lm: run OLS regression summary: obtain regression results coef: obtain estimated coefficients How to compute the predicted value of \(y\), \(\hat{y}\) predict The data set used for this exercise is Growth.xlsx from E4.1 of Stock and Watson...
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Lab 4: Simple Linear Regression with 1 Regressor
In this lab exercise, you will learn: How to make a scatter plot plot How to run an OLS regression in R lm: run OLS regression summary: obtain regression results coef: obtain estimated coefficients How to compute the predicted value of \(y\), \(\hat{y}\) predict The data set used for this exercise is Growth.xlsx from E4.1 of Stock and Watson...
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Lab 3: Statistics (with solutions)
In this lab exercise, you will learn: How to select a subset of data subset How to compute confidence intervals using R qnorm, qt, qf t.test How to conduct a statistical test using R pnorm, pt, pf t.test The data set used for this exercise is CPS96_15 from E3.1 of Stock and Watson (2020, e4). This data contains 13,201 observations on full-ti...
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