Explanation Given: The given xy pairs are (4, 5), (6, 8), (5, 3), (5, 6). 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 4 5 20 16 25 6 8 48 36 64 5 3 15 25 9 5 6 30 25 36 ∑ x = 20 ∑ y = 22 ∑ x y = 113 ∑ x 2 = 102 ∑ y 2 = 134 Substitute the known values in r = n ∑ x y − ( ∑ x ) ( ∑ y ) n ( ∑ x 2 ) − ( ∑ x ) 2 n ( ∑ y 2 ) − ( ∑ y ) 2

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ISBN: 9780134506470

Author: Pirnot

Publisher: PEARSON

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Chapter 14.5, Problem 8E

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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 7E

Chapter 14.5, Problem 9E

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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 there is no significant linear correlation between x and y for the given confident level.

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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 there is no significant linear correlation between x and y for the given confident level.

Concept explainers

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

Want to see the full answer?

Chapter 14 Solutions

To find:

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