[SOLVED] CS计算机代考程序代写 # BS1033 Lecture 1 Analysis Part 2

# BS1033 Lecture 1 Analysis Part 2
# Author: Chris Hansman
# Email: [email protected]
# Date : 07/01/19
# Installing Packages
#install.packages(“tidyverse”)

# Loading Libraries
library(tidyverse)

#Reading OLS Data
ols_basics<-read_csv(“ols_basics.csv”)#Scatter Plot of OLS Example Dataggplot(data = ols_basics ) + geom_point(aes(x = X, y = Y)) +ggsave(“ols_scatter.pdf”)#Scatter Plot of OLS Example Data with Regression Lineggplot(data = ols_basics ) + geom_point(aes(x = X, y = Y))+geom_smooth( aes(x = X, y = Y), method=’lm’,formula=y~x) +ggsave(“ols_scatter_regline.pdf”)# Example Linear Regressionols_v1<-lm(Y~X, data= ols_basics)summary(ols_v1)#Scatter Plots for Non-Linear CEF with Regression Line:ggplot(data = ols_basics ) + geom_point(aes(x = X, y = Y_nl)) +geom_smooth( aes(x = X, y = Y_nl), method=’lm’,formula=y~x) +ggsave(“ols_scatter_lfit_nl.pdf”)#Reading S and P Datas_p_price<-read_csv(“s_p_price.csv”)s_p_price %>%
summarize(mean(price))

#Conditional Means for IT Sector:
s_p_price %>%
group_by(IT) %>%
summarize(mean_price = sprintf(“%0.3f”,mean(price)))

#Regressions for IT Sector:
ols_it<-lm(price~IT, data= s_p_price)summary(ols_it)#Conditional Means for All Sectors:s_p_price %>%
group_by(sector) %>%
summarize(mean_price = sprintf(“%0.3f”,mean(price)))

#Regressions for All Sectors:
ols_sector<-lm(price~as.factor(sector), data= s_p_price)summary(ols_sector)