MTCARS_CASESTUDY

Let us create a model on mtcars dataset

data(mtcars)

View(mtcars)
str(mtcars)

## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

To create a model first thing is call the data from the library

Next is view is to view the table

To know the internal struture of the data

Let us create a variable - miles_per_gallon and cylinder

miles_per_gallon <- mtcars[,1]
cylinder <- mtcars$cyl

Here [] is used to create a variable called miler_per_gallon and that should be available in global Environment.

Here $ symbol is used to create the variable and should be available in global Environment.

Let us use simple regression

model1 <- lm(miles_per_gallon ~cylinder)
model1

## 
## Call:
## lm(formula = miles_per_gallon ~ cylinder)
## 
## Coefficients:
## (Intercept)     cylinder  
##      37.885       -2.876

We created lm, lm is used for creating relationship in Regression.

Given sample used, If a car ran hypothetically with no cylinder, it would give 37.885 miles_per_gallon of gasoline it uses. With each cylinder more in the car as, its mileage will decrease 2.876miles_per_gallon.

A car with 8 cylinders will have a predicted mileage of ?

we are creating a predictive model1

criteria : A car having 8 cylinders

To check: the mileage/performance of cars having 8 cylinders

  predict(model1, newdata=data.frame(cylinder=8))

##        1 
## 14.87826

For predictive analysis we use predict function for the outcome.We are predicting for 8 cylinders.

Therefore a car with 8 cylinder will have predicted mileage of 14.87826 miles_per_gallon.

A car with 6 cylinders will have a predicted mileage of ?

we are creating a predictive model1

criteria : A car having 6 cylinders

To check: the mileage/performance of cars having 6 cylinders

   predict(model1, newdata=data.frame(cylinder=6))

##        1 
## 20.62984

Again used the Predict function as now we are predicting for 6 cylinders.

Therefore a car with 6 cylinder will have predicted mileage of 20.62984 miles_per_gallon.

A car with 4 cylinders will have a predicted mileage of ?

we are creating a predictive model1

criteria : A car having 4 cylinders

To check: the mileage/performance of cars having 4 cylinders

predict(model1, newdata=data.frame(cylinder=4))

##        1 
## 26.38142

Again used the Predict function as now we are predicting for 4 cylinders.

Therefore a car with 4 cylinder will have predicted mileage of 26.38142 miles_per_gallon.

let us create some visuals

plot <- plot(cylinder,miles_per_gallon,type = "p",main = "Gas consumption as explained by number of cylinders",
             sub ="General Information", xlab = "# of cylinders", ylab ="Miles (US) per gallon",col="firebrick" )
abline(model1)

The plot function is used to draw points in diagram/ For graphical representation of Model 1 and for trend line we used abline function for model 1 plot.

create a model using multiple regression model

variables to be used mpg,cyl, am

create model2 using above three variables

Let us create variable <- am

am <- mtcars$am

model2 <- lm(miles_per_gallon~cylinder+ am)
model2

## 
## Call:
## lm(formula = miles_per_gallon ~ cylinder + am)
## 
## Coefficients:
## (Intercept)     cylinder           am  
##      34.522       -2.501        2.567

Here a new variable is created am for new model2 creation, again lm is used for creating relationship.

In this model,along with the number of cylinders, we include the variable am(0 if the car has automatic transmission, 1 if is manual) 1.If the car is automatic and the number of cylinders is 0, the hypothetical mileage of it would be 34.522 miles_per_gallon. 2.If everything else remain constant, per each cylinder more than the car has, it will decrease by 2.501miles_per_gallon. 3.If everything else remain constant, If the car is manual, its mileage will increase by 2.567 miles_per_gallon.