decision science
DESCRIPTION
factor analysisTRANSCRIPT
Presentation On Theory Of Decision Science
regression model with three explanatory variable
Of Life satisfaction.(Y)
Presented by:- ▪ Suhail Manjardekar 05
▪ Amar Itagi 47
▪ Shardul Thakker 38
▪ Kunal Sharma 61
Independent variables (X’s)
▪ Income (X1)
▪ Sprit (X2)
▪ Socio economic status of parents (X3)
Data collection
N Y X1 X2 X3
Data analysis using SPSS
1-fitting the regression model
2-Overall significance of the model & ANOVA table
Interpretation of the model
▪ Apriority Analysis.
▪ Statistical Analysis.
▪ Econometric Analysis.
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).
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.
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.
Econometric Analysis
1-AUTOCORELATION
Since it lies between du and 2,there is no autocorrelation.
0 0.998 1.676 2 2.324 3.012 4
0 du dl 2 4-du 4-dl 4
d=1.821
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.