This document presents a regression model analyzing the relationship between life satisfaction (dependent variable) and three explanatory variables: income, spirit, and socioeconomic status of parents. Data was collected and analyzed using SPSS to fit the regression model and test its significance. The a priori, statistical, and econometric analyses found that the regression model was not significant and that the coefficients were insignificant, indicating the variables were not good predictors of life satisfaction. Tests also showed no issues with autocorrelation or multicollinearity in the model.

1. Presentation On Theory Of
Decision Science
regression model with three
explanatory variable
Of
Life satisfaction.(Y)

2. Presented by:- ▪ Suhail Manjardekar 05
▪ Amar Itagi 47
▪ Shardul Thakker 38
▪ Kunal Sharma 61

3. Independent variables (X’s)
▪ Income (X1)
▪ Sprit (X2)
▪ Socio economic status of parents (X3)

4. Data collection
N Y X1 X2 X3

5. Data analysis using SPSS

6. 1-fitting the regression model

7. 2-Overall significance of the model & ANOVA table

8. Interpretation of the model
▪ Apriority Analysis.
▪ Statistical Analysis.
▪ Econometric Analysis.

9. Apriority Analysis
It is Assumed that
▪ Life satisfaction (Y) is α to Income (X1)
▪ Life satisfaction (Y) is α to Spirit (X2).
▪ Life satisfaction (Y) is α to Socio-economic status of parents(X3).

10. Statistical Analysis
▪ The regression model is “Y=16.472+0.123 X1+0.158 X2+0.174 X3”
1-ELASTICITY
▪ η1 (β1)= 0.169 under elastic (<1).
▪ η2 (β2)= 0.179 under elastic(<1).
▪ η3 (β3)= 0.1797 under elastic(<1).
2-OVER ALL SIGNIFICANCE OF THE MODEL
 R square=0.264
 Since R square < 0.7 the overall significance of the model is not good.

11. 3-ANOVA table
▪ Since F value < F table therefore do not reject H0 and conclude that
β1,β2,β3 are insignificant i.e. they are 0, and model is not good.
4-INDIVIDUAL TEST(t-test @5%level of significance)
▪ β0=1.676 < 2.120 (16) conclude that β0 is insignificant.
▪ β2=1.698 < 2.120 (16) conclude that β1 is insignificant.
▪ β3=0.982 < 2.120 (16) conclude that β2 is insignificant.
▪ β1=0.978 < 2.120 (16) conclude that β3 is insignificant.

12. Econometric Analysis
1-AUTOCORELATION
d=1.821
0 du dl 2 4-du 4-dl 4
0 0.998 1.676 2 2.324 3.012 4
 Since it lies between du and 2,there is no autocorrelation.

13. 2-MULTICOLINEARITY
▪ Since in F test and individual test we are not rejecting H0
i.e. in both the cases the β’s are insignificant or zero; there
is no multicolinearity in the model.
Also
▪ VIF (variance inflation factors) for β0=1.062, β2=1.091,
β3=1.037 are < 10 therefore there is no multicolinearity
exsist in the model.