The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. Commute Time (in minutes) 7 15 23 37 54 65 103 Well-Being Score 69.7 68.1 67.3 67.1 66.2 65.1 63.8 E Click the icon to view the critical values for the correlation coefficient. (c) Determine the linear correlation coefficient between commute time and well-being score. r= (Round to three decimal places as needed.) (d) Does a linear relation exist between the commute time and well-being index score? O A. Yes, there appears to be a positive linear association because r is positive and is greater than the critical value. O B. Yes, there appears to be a negative linear association because r is negative and is less than the opposite of the critical value O C. Yes, there appears to be a positive linear association because r is positive and is less than the critical value. O D. No, there is no linear association since r is positive and is less than the critical value.
The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. Commute Time (in minutes) 7 15 23 37 54 65 103 Well-Being Score 69.7 68.1 67.3 67.1 66.2 65.1 63.8 E Click the icon to view the critical values for the correlation coefficient. (c) Determine the linear correlation coefficient between commute time and well-being score. r= (Round to three decimal places as needed.) (d) Does a linear relation exist between the commute time and well-being index score? O A. Yes, there appears to be a positive linear association because r is positive and is greater than the critical value. O B. Yes, there appears to be a negative linear association because r is negative and is less than the opposite of the critical value O C. Yes, there appears to be a positive linear association because r is positive and is less than the critical value. O D. No, there is no linear association since r is positive and is less than the critical value.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2BGP
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Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Question
Transcribed Image Text:The data in the table to the right are based on the results of a survey comparing the commute time of adults to
their score on a well-being test. Complete parts (a) through (d) below.
Commute Time
Click the icon to view the critical values for the correlation coefficient.
(in minutes)
15
23
37
54
65
103
Well-Being Score
69.7
68.1
67.3
67.1
66 2
65 1
63.8
(c) Determine the linear correlation coefficient between commute time and well-being score.
r=
(Round to three decimal places as needed.)
(d) Does a linear relation exist between the commute time and well-being index score?
O A. Yes, there appears to be a positive linear association because r is positive and is greater than the critical value.
O B. Yes, there appears to be a negative linear association because r is negative and is less than the opposite of the critical value.
O C. Yes, there appears to be a positive linear association becauseris positive and is less than the critical value.
O D. No, there is no linear association since r is positive and is less than the critical value.
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