Textbook ExpertVerified Tutor
16 Nov 2021
Given information
The following table shows data on average per capita coffee consumption and heart disease rate in a random sample of 
countries:
Step-by-step explanation
Step 1.
The correlation coefficient, or Pearson product-moment correlation coefficient (PMCC) is a numerical value which lies between 
and 
and expresses the strength of linear relationship between two variables. When 
is closer to , indicates a strong positive relationship. Value of 
indicates that there is no relationship. Values close to defines a strong negative relationship between the two variables.
Simple linear regression is a way to describe a relationship between two variables through an equation of a straight line.
By using the following formula we derive the equation for the line of best fit: 
Here,
Unlock all Textbook Solutions
Already have an account? Log in
Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208
Solutions
Chapter
Section
- Problem 57a
- Problem 57c
- Problem 57d
- Problem 57e
- Problem 62
- Problem 63
- Problem 64
- Problem 65
- Problem 66
- Problem 67
- Problem 68
- Problem 69a
- Problem 69b
- Problem 69c
- Problem 69d
- Problem 69e
- Problem 69f
- Problem 69g
- Problem 70a
- Problem 70b
- Problem 70c
- Problem 70d
- Problem 70e
- Problem 70f
- Problem 70g
- Problem 70h
- Problem 70i
- Problem 70j
- Problem 70k
- Problem 71a
- Problem 71b
- Problem 71c
- Problem 71d
- Problem 71e
- Problem 71f
- Problem 71g
- Problem 71h
- Problem 72a
- Problem 72b
- Problem 72c
- Problem 72d
- Problem 72e
- Problem 72f
- Problem 72g
- Problem 72h
- Problem 72i
- Problem 72j
- Problem 73a
- Problem 73b
- Problem 73c
- Problem 73d
- Problem 73e
- Problem 73f
- Problem 73g
- Problem 73h
- Problem 74a
- Problem 74b
- Problem 74c
- Problem 74d
- Problem 74e
- Problem 74f
- Problem 74g
- Problem 74h
- Problem 74i
- Problem 74j
- Problem 75a
- Problem 75b
- Problem 75c
- Problem 75d
- Problem 75e
- Problem 75f
- Problem 76a
- Problem 76b
- Problem 76c
- Problem 76d
- Problem 76e
- Problem 76f
- Problem 77a
- Problem 77b
- Problem 77c
- Problem 77d
- Problem 77e
- Problem 78a
- Problem 78b
- Problem 78ci
- Problem 78cii
- Problem 78ciii
- Problem 78civ
- Problem 78d
- Problem 79
- Problem 80c
- Problem 83a
- Problem 83b
- Problem 83c
- Problem 83d
- Problem 83e
- Problem 83f
- Problem 83g
- Problem 83h
- Problem 83i
- Problem 83j
- Problem 83k