title: “Simple”

author: “Udit Gupta”

date: “29 May 2018”

output: html_document

# Data Preprocessing Template

# Importing the dataset
dataset = read.csv('Salary_Data.csv')

# Splitting the dataset into the Training set and Test set
# install.packages('caTools')
library(caTools)

## Warning: package 'caTools' was built under R version 3.4.4

set.seed(123)
split = sample.split(dataset$Salary, SplitRatio = 2/3)
training_set = subset(dataset, split == TRUE)
test_set = subset(dataset, split == FALSE)

# Feature Scaling
# training_set = scale(training_set)
# test_set = scale(test_set)

#Fitting  Simple Linear Regression to the training set

regressor =lm(formula = Salary ~ YearsExperience,
              data=training_set)
summary(regressor)

## 
## Call:
## lm(formula = Salary ~ YearsExperience, data = training_set)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -7325.1 -3814.4   427.7  3559.7  8884.6 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        25592       2646   9.672 1.49e-08 ***
## YearsExperience     9365        421  22.245 1.52e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5391 on 18 degrees of freedom
## Multiple R-squared:  0.9649, Adjusted R-squared:  0.963 
## F-statistic: 494.8 on 1 and 18 DF,  p-value: 1.524e-14

# Predicting the test results
y_pred=predict(regressor, newdata = test_set)