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Given below are seven observations collected in a regression study on two variab

ID: 3223969 • Letter: G

Question

Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable). Use Excel's Regression Tool to answer the following questions.

x

y

2

12

3

  9

6

  8

7

  7

8

  6

7

  5

9

  2

a.

What is the estimated regression equation?

b.

Perform a t-test and determine whether or not x and y are related. Use a = 0.05.

c.

Perform an F-test and determine whether or not x and y are related. Use a = 0.05.

d.

Find and interpret the coefficient of determination.

STEP BY STEP SOLUTION PLEASE!

x

y

2

12

3

  9

6

  8

7

  7

8

  6

7

  5

9

  2

Explanation / Answer

(a)

We will find an equation of the regression line in 4 steps.

Step 1: Find XY and X as it was done in the table below.

Step 2: Find the sum of every column:

X=42 , Y=49 , XY=249 , X2=292

Step 3: Use the following equations to find a and b:

a=YX2XXY/nX2(X)2=4929242249729242213.75

b=nXYXY/nX2(X)2=724942497292(42)21.125

Step 4: Substitute a and b in regression equation formula

y = a + bx

y = 13.75 1.125x

(b)

Null Hypothesis (Ho): X and Y are not related

Alternative Hypothesis (H1): X and Y are related

For the given data we get the below values

Observed difference (Sample 1 - Sample 2): -1
Standard Deviation of Difference : 1.543

Test statistic

t = (Mean (X) – Mean (Y))/Sqrt ((s12/n1)+ (s22/n2))

Unequal Variances

DF : 11

By using the above (t) formula we get
T-Value -0.6481
Population 1 Population 2: P-Value = 0.5302

Conclusion: The result is not significant at p<0.05,

Therefore accept Null Hypothesis (Ho)

i.e X and Y are not related

(C)

Null Hypothesis (Ho): X and Y are not related

Alternative Hypothesis (H1): X and Y are related

Conclusion: Fcaluculated value < Fcritical value

i.e 0.42 < 4.7472

Therefore we accept Null Hypothesis (Ho)

i.e X and Y are not related

(d)

Step 1: Find XY , X2 and Y2 as it was done in the table below.

Step 2: Find the sum of every column to get:

X=42 , Y=49 , XY=249 , X2=292 , Y2=403

Step 3: Use the following formula to work out the correlation coefficient.

r = (nXYXY)/sqrt[nX2(X)2][nY2(Y)2]

r = 0.9186

The coefficient of determination r2 = 0.8438

Interpretation:

Since r2 is between 0 and 1 " r2x100 percent of the variation in y is reduced by taking into account predictor X".  

X Y XY XX 2 12 24 4 3 9 27 9 6 8 48 36 7 7 49 49 8 6 48 64 7 5 35 49 9 2 18 81
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