Explanation Given: The given xy pairs are (3, 5), (7, 8), (4, 6), (6, 7). Definition used: If we have pairs of data for two variables x and y , the linear correlation coefficient for these data, denoted by r , is given by the formula r = n ∑ x y − ( ∑ x ) ( ∑ y ) n ( ∑ x 2 ) − ( ∑ x ) 2 n ( ∑ y 2 ) − ( ∑ y ) 2 , where n is the number of pairs of data we have for x and y . Calculation: Consider the given xy pairs. The computations to calculate correlation coefficient is shown below x y xy x 2 y 2 3 5 15 9 25 7 8 56 49 64 4 6 24 16 36 6 7 42 36 49 ∑ x = 20 ∑ y = 26 ∑ x y = 137 ∑ x 2 = 110 ∑ y 2 = 174 Substitute the known values in r = n ∑ x y − ( ∑ x ) ( ∑ y ) n ( ∑ x 2 ) − ( ∑ x ) 2 n ( ∑ y 2 ) − ( ∑ y ) 2

6th Edition

ISBN: 9780134434681

Author: Tom Pirnot

Publisher: PEARSON

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Chapter 14.5, Problem 7E

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Whether we can be 95% or 99% confident that there is significant linear correlation between x and y.

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Chapter 14.5, Problem 6E

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Whether we can be 95% or 99% confident that there is significant linear correlation between x and y .

Solution Summary: The author explains that they can be 95% or 99% confident that there is significant linear correlation between x and y.

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To find:

Whether we can be 95% or 99% confident that there is significant linear correlation between x and y.

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Chapter 14 Solutions

Whether we can be 95% or 99% confident that there is significant linear correlation between x and y .

Solution Summary: The author explains that they can be 95% or 99% confident that there is significant linear correlation between x and y.

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To find: Whether we can be 95% or 99% confident that there is significant linear correlation between x and y.

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Chapter 14 Solutions

To find:

Whether we can be 95% or 99% confident that there is significant linear correlation between x and y.