RAGUL DATA ANALYST-MULTI LINEAR REGRESSION

library(readxl)

Regression_Analysis <- read_excel("C:/Users/Hxtreme/Desktop/Regression_BATCH2.xlsx")

IMPORTED THE DATA USING “IMPORT DATASET” AVAILABLE IN THE ENVIRONMENT COLUMN. THEN COPIED THE CODE PREVIEW FROM THE IMPORT DATA SECTION.

View(Regression_Analysis)

THIS FUNCTION HELPS US TO VIEW THE IMPORTED DATA

summary(Regression_Analysis)

    Student      School_Ranking       GPA          Experience   
 Min.   : 1.00   Min.   :15.00   Min.   :2.760   Min.   :2.000  
 1st Qu.:10.75   1st Qu.:45.75   1st Qu.:3.033   1st Qu.:5.000  
 Median :20.50   Median :67.00   Median :3.155   Median :6.000  
 Mean   :20.50   Mean   :59.88   Mean   :3.233   Mean   :5.975  
 3rd Qu.:30.25   3rd Qu.:76.50   3rd Qu.:3.350   3rd Qu.:7.000  
 Max.   :40.00   Max.   :89.00   Max.   :3.850   Max.   :9.000  
     Salary     
 Min.   :71040  
 1st Qu.:76913  
 Median :78670  
 Mean   :78721  
 3rd Qu.:80600  
 Max.   :87000  

THIS FUNCTION SHOWS THE OVERALL SUMMARY OF THE TABLE.

str(Regression_Analysis)

Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   40 obs. of  5 variables:
 $ Student       : num  1 2 3 4 5 6 7 8 9 10 ...
 $ School_Ranking: num  78 56 23 67 56 78 68 89 37 67 ...
 $ GPA           : num  2.92 3.84 3.04 3.2 3.61 2.99 3.78 3.2 3.42 3.05 ...
 $ Experience    : num  3 9 6 6 7 5 8 5 7 5 ...
 $ Salary        : num  73590 87000 76970 79320 79530 ...

THIS FUNCTION SHOWS THE STRUCTURE OF THE TABLE.

THIS FUNCTION SHOWS THE ENTIRE DATA IN A PLOT GRAPH.

THIS FUNCTION SHOWS THE SCATTER PLOT GRAPH FOR THE FIRST TWO VARIABLES IN THE DATA.

THE “par” FUNCTION IS USED TO SET THE MULTIFRAME GRAPHICAL PARAMETERS.

cc

                   Student School_Ranking        GPA Experience      Salary
Student         1.00000000      0.0582101 -0.1262402 0.04395596 -0.00261919
School_Ranking  0.05821010      1.0000000  0.2051312 0.20250931  0.23429048
GPA            -0.12624017      0.2051312  1.0000000 0.65904413  0.73788910
Experience      0.04395596      0.2025093  0.6590441 1.00000000  0.78580114
Salary         -0.00261919      0.2342905  0.7378891 0.78580114  1.00000000

THIS FUNCTON HELPS TO DO THE CORRELATION ANALYSIS FOR THE GIVEN DATA.

THE FUNCTION “library” IS USED TO CALL THE CORRPLOT GRAPH FUNCTION,WHICH IS BASED FROM THE DERIVED CORRELATION ANALYSIS OF THE GIVEN DATA.

linearmodel

Call:
lm(formula = Salary ~ GPA + Experience + School_Ranking + Student, 
    data = Regression_Analysis)

Coefficients:
   (Intercept)             GPA      Experience  School_Ranking  
     52751.870        5534.006        1232.513           9.442  
       Student  
         7.064  

THIS FUNCTION IS USED TO INSERT THE FORMULA FOR CALCUATING THE REGRESSION ANALYSIS FROM THE GIVEN DATA.

summary(linearmodel)

Call:
lm(formula = Salary ~ GPA + Experience + School_Ranking + Student, 
    data = Regression_Analysis)

Residuals:
    Min      1Q  Median      3Q     Max 
-6359.4  -736.0   306.7  1392.8  4440.1 

Coefficients:
                Estimate Std. Error t value Pr(>|t|)    
(Intercept)    52751.870   4928.281  10.704 1.39e-12 ***
GPA             5534.006   1785.345   3.100 0.003811 ** 
Experience      1232.513    294.651   4.183 0.000183 ***
School_Ranking     9.442     18.450   0.512 0.612031    
Student            7.064     31.929   0.221 0.826188    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2273 on 35 degrees of freedom
Multiple R-squared:  0.7058,    Adjusted R-squared:  0.6722 
F-statistic: 20.99 on 4 and 35 DF,  p-value: 6.703e-09

THIS FUNCTION GIVES THE ENTIRE SUMMARY OF THE WHOLE REGRESSION ANALYSIS DONE ON THE DERIVED DATA.

linearmodel

Call:
lm(formula = Salary ~ GPA + Experience, data = Regression_Analysis)

Coefficients:
(Intercept)          GPA   Experience  
      53295         5540         1257  

BASED ON THE P-VALUE FROM THE REGRESSION ANALYSIS,‘GPA & EXPERIENCE’ VARIABLES ARE THE ONES CLOSELY RELATED TO THE DEPENDENT VARIABLE ‘SALARY’.

my_predict_result

       1 
87280.72 

WITH THE CALCULATED REGRESSION EQUATION,WE ARE ABLE TO PREDICT THE SALARY OF A STUDENT WHO HAS A ‘EXPERIENCE=5,GPA=5’.