Data found here please only use matlab and show codeSolution

Data found here.

please only use matlab and show code

Solution

data on trafic charactersistic at 10 intersections in Madras. to fit the regression and test the significance of the regression coefficients.

y= median speed in km/h

x1= road width in meter.

x2= trafic volumein vechiles per lane per hours.

here y is dependent variable and x1 , x2 are indepedent variable.

Coefficients^a

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

25.613

10.424

2.457

.044

x1

.184

.124

.302

1.488

.180

x2

-.016

.004

-.795

-3.916

.006

a. Dependent Variable: y

ANOVA^b

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

163.571

2

81.786

8.654

.013^a

Residual

66.154

7

9.451

Total

229.725

9

a. Predictors: (Constant), x2, x1

b. Dependent Variable: y

The calculated p- value is 0.013 which is less than the 0.05 its means that null hypothesis is rejected i.e. all coefficient is not equal to zero.

ANOVA^b

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

18.616

1

18.616

.705

.425^a

Residual

211.109

8

26.389

Total

229.725

9

a. Predictors: (Constant), x1

b. Dependent Variable: y

Coefficients^a

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

14.444

16.754

.862

.414

x1

.173

.206

.285

.840

.425

a. Dependent Variable: y

In the regression model the calculated p- value in ANOVA table is 0.425 which is greater than 0.05 its means null hypothesis is accepted and we say that all =0. For the given set of data.

ANOVA^b

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

142.634

1

142.634

13.102

.007^a

Residual

87.091

8

10.886

Total

229.725

9

a. Predictors: (Constant), x2

b. Dependent Variable: y

Coefficients^a

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

40.370

3.455

11.686

.000

x2

-.016

.004

-.788

-3.620

.007

a. Dependent Variable: y

In the regression model the calculated p- value in ANOVA table is 0.007 which is less than 0.05 its means null hypothesis is rejected and we say that is not equal to 0 . For the given set of data.

Model

R² value

Adjusted R² value

Model (a)

0.712

0.630

Model (b)

0.081

-0.034

Model (c)

0.621

0.573

On the basis of the analysis , the R2 is maximum of the model (a) so model (a) is best model for the given data set.

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	25.613	10.424		2.457	.044
x1	.184	.124	.302	1.488	.180
x2	-.016	.004	-.795	-3.916	.006
a. Dependent Variable: y