Regression Statistics Multiple R 0.94898 R Square 0.90056 Adjusted R Square 0.82

Question

Regression Statistics

Multiple R

0.94898

R Square

0.90056

Adjusted R

Square

0.82101

Standard Error

6.24921

Observations

10

ANOVA

df

SS

MS

F

Significance

F

Regression

4

1768.3366

442.0841

11.3202

0.0101

Residual

5

195.2634

39.0527

Total

9

1963.6000

Coefficients

Standard

Error

t Stat

P-value

Lower 95%

Intercept

48.3628

14.1772

3.4113

0.0190

11.9192

weight

-21.3770

9.7575

-2.1908

0.0300

-46.4595

height

-12.4787

7.3110

-1.7068

0.1486

-31.2723

power

-4.2240

8.8810

-0.4756

0.6544

-27.0534

speed

0.2849

0.3917

0.7272

0.4997

-0.7221

Using the above Excel summary output results, answer the following questions.

                     a) How many samples were collected to generate this data?

    b) What is the correlation for this multiple regression, and what does it indicate?

Please show detailed calculations.

Regression Statistics

Multiple R

0.94898

R Square

0.90056

Adjusted R

Square

0.82101

Standard Error

6.24921

Observations

10

ANOVA

df

SS

MS

F

Significance

F

Regression

4

1768.3366

442.0841

11.3202

0.0101

Residual

5

195.2634

39.0527

Total

9

1963.6000

Coefficients

Standard

Error

t Stat

P-value

Lower 95%

Intercept

48.3628

14.1772

3.4113

0.0190

11.9192

weight

-21.3770

9.7575

-2.1908

0.0300

-46.4595

height

-12.4787

7.3110

-1.7068

0.1486

-31.2723

power

-4.2240

8.8810

-0.4756

0.6544

-27.0534

speed

0.2849

0.3917

0.7272

0.4997

-0.7221

Explanation / Answer

a) yo need 1 sample of 10

b)the correlation for this multiple regression is 94% and it is a measure of how well a given variable can be predicted using a linear function of a set of other variables. In this time it is a very good prediction.

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