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sants to test her claim that a significant linear relationship exists 2. A statistics instractor the final exam score in Stat
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Answer #1

a.

From the data,

\sum x = 677

\sum y = 666

\sum x^2 = 58169

\sum y^2 = 56094

\sum xy = 57086

S_{xx} = \sum x^2 - (\sum x)^2 / n = 58169 - 677^2 / 8 = 877.875

S_{yy} = \sum y^2 - (\sum y)^2 / n = 56094 - 666^2 / 8 = 649.5

S_{xy} = \sum xy - (\sum x \sum y) / n = 57086 - (677 * 666) / 8 = 725.75

Correlation Coefficient, r = S_{xy} / \sqrt{S_{xx}S_{yy}} = 725.75 / \sqrt{877.875 * 649.5} = 0.9611

(b)

Null hypothesis H0: r = 0

Alternative hypothesis H1: r \ne 0

Claim is that there exists a linear relationship between scores of Stat101 and Stat102.

(c)

Degree of freedom = n - 2 = 8 - 2 = 6

Critical value of t at df = 6 and significance level of 0.05 is \pm 2.45

We reject H0 if t < -2.45 or t > 2.45

(d)

Test statistic, t = r \sqrt{n-2} / \sqrt{1-r^2}

= 0.9611 \sqrt{8-2} / \sqrt{1-0.9611^2}

= 8.52

For two tail test, P-value = 2 * p(t > 8.52) = 0.00014

(e)

Since p-value is less than 0.05 significance level, we reject null hypothesis H0 and conclude that there is significant evidence that r \ne 0.

(f)

There is a there exists a significant linear relationship between scores of Stat101 and Stat102.

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