linear regression model

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Including Code

You can include R code in the document as follows:

airData<-data("airquality")
View(airData)

#check data summary
summary(airData);

##    Length     Class      Mode 
##         1 character character

#dataset headers name

names(airData)

## NULL

Including Plots

Check data quality using #single linear regression model

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot. #multiple regression model

#create multiple variable regression model
coPlot<-coplot(Ozone~Solar.R|Wind,panel=panel.smooth,airquality)

## 
##  Missing rows: 5, 6, 10, 11, 25, 26, 27, 32, 33, 34, 35, 36, 37, 39, 42, 43, 45, 46, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 72, 75, 83, 84, 96, 97, 98, 102, 103, 107, 115, 119, 150

createModel2<-lm(formula=Ozone~Solar.R*Wind,airquality)
plot(createModel2)

summary(airquality$Wind)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.700   7.400   9.700   9.958  11.500  20.700

summary(airquality$Solar.R)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##     7.0   115.8   205.0   185.9   258.8   334.0       7

solarQuarter1=mean(airquality$Solar.R,na.rm=T)
solarQuarter2=200
solarQuarter3=300

#predict values according to uater

predict1<-predict(createModel2,data.frame(Solar.R=solarQuarter1,Wind=1:20))
predict2<-predict(createModel2,data.frame(Solar.R=solarQuarter2,Wind=1:20))
predict3<-predict(createModel2,data.frame(Solar.R=solarQuarter3,Wind=1:20))

plot(Solar.R~Wind,airquality)
lines(1:20,predict1)
lines(1:20,predict2)
lines(1:20,predict3)