vaibhav kumar 531

7/28/2019 Vaibhav Kumar 531

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WHAT FACTOR ARE RESPONSIBLE

FOR AN INDIAN DEFENCE TO

SHIFT FROM USING AN

ORDINARY OLD WEAPON TO A

MODERN NEW WEAPON IN

PRESENT SENARIO ?

(MULTIPLE REGRESSION

ANANLYSIS)

BY-

VAIBHAV KUMAR

(531)

MBA TECH EXTC


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Descriptive Statistics

Mean Std. Deviation N

Real Investment .2033 .03418 15

Constant 1.0000 .00000 15

Trend 8.0000 4.47214 15

Real GNP 1.2873 .16027 15

Interest Rate 7.4527 2.81224 15

Inflation Rate 6.6513 1.94688 15

The minimum ratio of valid cases to independent variables for multiple regressions is 5 to

1. Which is just 5:1 in this case So we except this data and we proceeds with other analysis.

Correlations

Real

InvestmentConstant Trend Real GNP Interest Rate Inflation Rate

Pearson Correlation Real Investment

Constant

Trend

Real GNP

Interest Rate

Inflation Rate

1.000 . .750 .863 .587 .478

. 1.000 . . . .

.750 . 1.000 .979 .804 .635

.863 . .979 1.000 .804 .636

.587 . .804 .804 1.000 .724

.478 . .635 .636 .724 1.000

Sig. (1-tailed) Real Investment

Constant

Trend

Real GNP

Interest Rate

Inflation Rate

. .000 .001 .000 .011 .036

.000 . .000 .000 .000 .000

.001 .000 . .000 .000 .005

.000 .000 .000 . .000 .005

.011 .000 .000 .000 . .001

.036 .000 .005 .005 .001 .

N Real Investment

Constant

Trend

Real GNP

Interest Rate

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15


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Correlations

Real

InvestmentConstant Trend Real GNP Interest Rate Inflation Rate

Pearson Correlation Real Investment

Constant

Trend

Real GNP

Interest Rate

Inflation Rate

1.000 . .750 .863 .587 .478

. 1.000 . . . .

.750 . 1.000 .979 .804 .635

.863 . .979 1.000 .804 .636

.587 . .804 .804 1.000 .724

.478 . .635 .636 .724 1.000

Sig. (1-tailed) Real Investment

Constant

Trend

Real GNP

Interest Rate

Inflation Rate

. .000 .001 .000 .011 .036

.000 . .000 .000 .000 .000

.001 .000 . .000 .000 .005

.000 .000 .000 . .000 .005

.011 .000 .000 .000 . .001

.036 .000 .005 .005 .001 .

N Real Investment

Constant

Trend

Real GNP

Interest Rate

Inflation Rate

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

15 15 15 15 15 15

Variables Entered/Removed

Model Variables

Entered

Variables

RemovedMethod

1 Inflation Rate,Trend, Interest

Rate, Real GNPa

.Enter

a. All requested variables entered.


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Model Summaryb

Model RR

Square

Adjusted R

Square

Std. Error of

the

Estimate

Change StatisticsDurbin-

WatsonR Square

Change

F

Changedf1 df2 Sig. F

Change

1 .986a .972 .961 .00671 .972 88.188 4 10 .000 1.964

a. Predictors: (Constant), Inflation Rate, Trend, Interest Rate, Real GNP

b. Dependent Variable: Real Investment

The Multiple R for the relationship between the set of independent variables and the dependent variable is 0.986,

which would be characterized as very strong using the rule of thumb than a correlation less than or equal to 0.20 is

characterized as very weak; greater than 0.20 and less than or equal to 0.40 is weak; greater than 0.40 and less

than or equal to 0.60 is moderate; greater than 0.60 and less than or equal to 0.80 is strong; and greater than 0.80 is

very strong.

The Durbin Watson statistics for this data is 1.964 which is within the required range (1.5 to 2.5) which means that the

errors are uncorrelated there is no autocorrelation.

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression

Residual

Total

.016 4 .004 88.188 .000a

.000 10 .000

.016 14

a. Predictors: (Constant), Inflation Rate, Trend, Interest Rate, Real GNP

b. Dependent Variable: Real Investment

The probability of the F statistic (88.188) for the overall regression relationship is


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Interest-.002 .001 -.191-1.908.085 .587 -.517 -

.100

.274 3.649

Inflation

Rate

-9.401E-5 .001 -.005 -.070.946 .478 -.022 -

.004

.468 2.137

a. Dependent Variable: Real Investment

Tolarence >0.2 => no multicolinearity

Tolerance of variable Xi is 1-Ri2* where Ri

2* is coefficient of determination for the prediction of variable i by

the other predictor variables. Tolerance value near to 0 indicate that the variable is highly predicted

(colinear) with other predictor variables

VIFVariance Inflation Factor should be less than 5

For the independent variable trends , real gnp ,interest , rate and inflation the probability of the t statistic

(-8.409 ,12.189 , -1.098 , -.070 respectively) for the b coefficient is


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Charts

This graph is almost Normal Distribution.


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Scatter plot

this graph indicates

no sign of hetro

dencity

vaibhav kumar 531

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