COURSE WORK QUESTIONS

Course Work

Introduction

Overall functions relates to import, this functions shows that how much the relationship is strong ,with respect to exchange rate & Gross domestic product(GDP). Here import is treated as independent variable and GDP & Exchange are treated as dependent variable.

Real Import Value:

=373742/100*100

=373742

This shows the real import value with respect to prices of year 2005.

Average Growth Rate of GDP, Imports & Exchange Rate

Average Growth Rates

%

GDP

2.43

Imports

8.78

Exchange rate

0.24

Average growth rate of GDP is 2.43 % for a period of 34 years. Import rate is approximately 8.78 %. And average exchange rate is .24 %

Regression

Regression is a sense of representation as a variable; the result is numerically correlated predictor variables. The dependent variable is also known as Y, called the dependent and is on the vertical axis (ordinate) of a graph. The predictor variable (s) is (are) also referred to as X, independent, prognostic, or explanatory variables. The horizontal axis (abscissa) is used to plot a graph X.

Equation: Y = b + mx

'm' is the slope, slope or regression coefficient

'b' is the intercept of the line at Y axis or regression constant

Y is a value for the outcome

x is a value for the predictor

Correlation Coefficient

The correlation coefficient, from the statistical concept of how good precedent to follow the predicted trend of the actual value of the trend measures. This is what a good forecast and the actual statistics, from a forecast model the "right" value of the benchmark. The correlation coefficient is a number between 0 and 1, if not the correlation coefficient between predicted value and actual value is equal to 0 or very low (predictive value than the random number is not good) since the relationship between predicted and actual Intensity of value added. Then the correlation coefficient will also increase. Provides a perfect combination of a factor of 1.0.Higher the correlation coefficient; the better will be the relationship.

Regression and correlation coefficients between Imports & Exchange Rate

Variables Entered/Removed

Model

Variables Entered

Variables Removed

Method

1

Imports

.

Enter

a. All requested variables entered.

b. Dependent Variable: Exc.rate

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.693a

.481

.464

6.40876

a. Predictors: (Constant), Imports

b. Dependent Variable:

Exchange rate

ANOVAs

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1216.195

1

1216.195

29.611

.000a

Residual

1314.309

32

41.072

Total

2530.504

33

a. Predictors: (Constant), Imports

b. Dependent Variable: Exchange rate

Coefficients'

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

79.118

1.998

39.602

.000

Imports

4.876E-5

.000

.693

5.442

.000

a. Dependent Variable: Exchange rate

Residuals Statistics

Minimum

Maximum

Mean

Std. Deviation

N

Predicted Value

80.5179

101.5962

88.1968

6.07078

34

Residual

-1.28875E1

12.66949

.00000

6.31091

34

Std. Predicted Value

-1.265

2.207

.000

1.000

34

Std. Residual

-2.011

1.977

.000

.985

34

a. Dependent Variable: Exchange Rate

Equation

y=.000048x+79.12

This equation shows that the relationship between Import & exchange rate is positive, and are dependable variables on one another. Secondly, above graph shows linear relationship between these two variables.

Regression and correlation coefficients between Imports and GDP

Variables Entered/Removed

Model

Variables Entered

Variables Removed

Method

1

Imports

.

Enter

a. All requested variables entered.

b. Dependent Variable: GDP

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.993a

.986

.986

23973.68627

a. Predictors: (Constant), Imports

b. Dependent Variable: GDP

ANOVAs

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1.320E12

1

1.320E12

2.297E3

.000a

Residual

1.839E10

32

5.747E8

Total

1.339E12

33

a. Predictors: (Constant), Imports

b. Dependent Variable: GDP

Coefficients'

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

501761.294

7473.409

67.140

.000

Imports

1.606

.034

.993

47.926

.000

a. Dependent Variable: GDP

Residuals Statistics

Minimum

Maximum

Mean

Std. Deviation

N

Predicted Value

5.4787E5

1.2423E6

8.0086E5

2.00011E5

34

Residual

-6.70668E4

3.99006E4

.00000

23607.65429

34

Std. Predicted Value

-1.265

2.207

.000

1.000

34

Std. Residual

-2.798

1.664

.000

.985

34

a. Dependent Variable: GDP

Equation

Y=1.60x+501761.29

Equation

y=1.60x+501761.29

This equation shows that the relationships between Import & GDP is positive, and are dependant variables. Secondly, above graph shows linear relationship between these two variables.

The relationship supports the understanding of this theory by showing a positive relation between the imports & exchange rate and ...