# Stat 200 HOMEWORK 7 complete

Lane Chap. 14

2. The formula for a regression equation is Y’ = 2X + 9.

a. What would be the predicted score for a person scoring 6 on X?

The predicted score for that person would be,

Y = 2*6+9 = 21

b. If someone’s predicted score was 14, what was this person’s score on X?

In this case Y = 14 thus,

14 = 2X+9

X = (14-9)/2 = 2.5

Thus the score on X was 2.5.

6. For the X, Y data below, compute:

a. r and determine if it is signiﬁcantly different from zero.

The obtained output from Minitab is given below,

Correlation: X, Y

Pearson correlation of X and Y = 0.849

P-Value = 0.032

From the above output we can see that the correlation coefficient between X and Y is 0.849 with corresponding P value 0.032. As the P value is smaller than the significance level of 0.05 so we can conclude that the correlation coefficient is significantly different from zero.

b. the slope of the regression line and test if it differs signiﬁcantly from zero.

Using the data analysis tool pack of Excel the obtained output is given below,

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.8492

R Square 0.7211

Adjusted R Square 0.6514

Standard Error 3.5028

Observations 6

2. The formula for a regression equation is Y’ = 2X + 9.

a. What would be the predicted score for a person scoring 6 on X?

The predicted score for that person would be,

Y = 2*6+9 = 21

b. If someone’s predicted score was 14, what was this person’s score on X?

In this case Y = 14 thus,

14 = 2X+9

X = (14-9)/2 = 2.5

Thus the score on X was 2.5.

6. For the X, Y data below, compute:

a. r and determine if it is signiﬁcantly different from zero.

The obtained output from Minitab is given below,

Correlation: X, Y

Pearson correlation of X and Y = 0.849

P-Value = 0.032

From the above output we can see that the correlation coefficient between X and Y is 0.849 with corresponding P value 0.032. As the P value is smaller than the significance level of 0.05 so we can conclude that the correlation coefficient is significantly different from zero.

b. the slope of the regression line and test if it differs signiﬁcantly from zero.

Using the data analysis tool pack of Excel the obtained output is given below,

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.8492

R Square 0.7211

Adjusted R Square 0.6514

Standard Error 3.5028

Observations 6

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