Project #158487 - homework

Mathematics Tutors

Subject Mathematics
Due By (Pacific Time) 12/04/2016 09:00 pm

1) Calculate the Pearson correlation coefficient for these two variables. Does its value support the hypothesized relationship?

 

 

EDUC

CHILDS

 (X -)

 (X -)2

 (Y -)

 (Y -) 2

(X -) (Y -)

 

16

0

 

 

 

 

 

 

12

1

 

 

 

 

 

 

12

3

 

 

 

 

 

 

6

6

 

 

 

 

 

 

14

2

 

 

 

 

 

 

14

2

 

 

 

 

 

 

16

2

 

 

 

 

 

 

12

2

 

 

 

 

 

 

17

2

 

 

 

 

 

 

12

3

 

 

 

 

 

 

14

4

 

 

 

 

 

 

13

0

 

 

 

 

 

 

12

1

 

 

 

 

 

 

12

2

 

 

 

 

 

 

12

3

 

 

 

 

 

 

11

1

 

 

 

 

 

 

12

2

 

 

 

 

 

 

11

2

 

 

 

 

 

 

12

0

 

 

 

 

 

 

12

2

 

 

 

 

 

 

12

3

 

 

 

 

 

 

12

4

 

 

 

 

 

 

12

1

 

 

 

 

 

 

14

0

 

 

 

 

 

 

12

3

 

 

 

 

 

 

ΣX=314

ΣY=51

Σ=

Σ=

Σ=

Σ=

Σ=

 

Mean X =

Mean Y =

Variance (Y)  =

 

Standard deviation (Y) =

Variance (X)  =

 

Standard deviation (X) =

Covariance (X,Y) =

*Answers may differ slightly due to rounding. Please review Table 13.4 on page 426 for details of calculations.

 

 

2.      2)  Calculate the least squares regression equation using education as a predictor variable. What is the value of the slope, b (5 pts)? What is the value of the intercept, a ?

 

 

 

4.    

5.      3) In this chapter, we used Table 13.4 to illustrate how to calculate the slope and intercept in the regression table. Using table 13.4 as a model, create a similar table using the data below for GNP per capita and the percentage willing to pay higher taxes (10 pts).

 

 

 

GNP per Capita (X)

% Willing to Pay Higher Taxes (Y)

(X -)

 (X -)2

(Y -)

(Y -) 2

(X -) (Y -)

19.71

24.0

 

 

 

 

 

4.99

29.1

 

 

 

 

 

24.28

12.0

 

 

 

 

 

18.71

34.3

 

 

 

 

 

32.35

37.2

 

 

 

 

 

2.42

17.3

 

 

 

 

 

3.84

34.7

 

 

 

 

 

24.78

51.9

 

 

 

 

 

14.60

31.1

 

 

 

 

 

34.31

22.8

 

 

 

 

 

10.67

17.1

 

 

 

 

 

2.66

29.9

 

 

 

 

 

14.10

22.2

 

 

 

 

 

25.58

19.5

 

 

 

 

 

39.98

33.5

 

 

 

 

 

29.24

31.6

 

 

 

 

 

ΣX=302.2

ΣY=448.2

ΣX=

Σ=

Σ=

Σ=

Σ=

Mean X =

Mean Y =

Variance (Y)  =

 

Standard deviation (Y) =

Variance (X)  =

 

Standard deviation (Y) =

Covariance (X,Y) =

 

 

6.  4) From the table that you created in #5, calculate a, b, and write out the regression equation (i.e., prediction equation)

 

 

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