Practice question #9 This scatterplot gives data for 30 drivers, where x is the driver’s age and y is how far they can see in feet. Answer the following questions about the relationship. a. Do you expect the correlation coefficient r to be a positive or a negative value? _________________ b. Given that r2 = .64, fill in the following: This means that ___________ % of the ________________________ in “Distance” is explained by the ____________________________ relationship between “Age” and “Distance.” c. Based on the above parts, what value do you expect r to be? _________________________ d. The equation for the line of best fit is y = −3.0x + 576.7, which is included on the graph. Approximately what distance in feet would you expect a 50-year old driver to see? e. Would it be appropriate to use our line of best fit to make a prediction about the distance seen by a 110 year old? ____________________ Doing so would be an example of what statistical concept? __________________________
Practice question #9 This scatterplot gives data for 30 drivers, where x is the driver’s age and y is how far they can see in feet. Answer the following questions about the relationship. a. Do you expect the correlation coefficient r to be a positive or a negative value? _________________ b. Given that r2 = .64, fill in the following: This means that ___________ % of the ________________________ in “Distance” is explained by the ____________________________ relationship between “Age” and “Distance.” c. Based on the above parts, what value do you expect r to be? _________________________ d. The equation for the line of best fit is y = −3.0x + 576.7, which is included on the graph. Approximately what distance in feet would you expect a 50-year old driver to see? e. Would it be appropriate to use our line of best fit to make a prediction about the distance seen by a 110 year old? ____________________ Doing so would be an example of what statistical concept? __________________________
Practice question #9 This scatterplot gives data for 30 drivers, where x is the driver’s age and y is how far they can see in feet. Answer the following questions about the relationship. a. Do you expect the correlation coefficient r to be a positive or a negative value? _________________ b. Given that r2 = .64, fill in the following: This means that ___________ % of the ________________________ in “Distance” is explained by the ____________________________ relationship between “Age” and “Distance.” c. Based on the above parts, what value do you expect r to be? _________________________ d. The equation for the line of best fit is y = −3.0x + 576.7, which is included on the graph. Approximately what distance in feet would you expect a 50-year old driver to see? e. Would it be appropriate to use our line of best fit to make a prediction about the distance seen by a 110 year old? ____________________ Doing so would be an example of what statistical concept? __________________________
This scatterplot gives data for 30 drivers, where x is the driver’s age and y is how far they can see in feet. Answer the following questions about the relationship.
a. Do you expect the correlation coefficient r to be a positive or a negative value? _________________
b. Given that r2 = .64, fill in the following: This means that ___________ % of the ________________________ in “Distance” is explained by the ____________________________ relationship between “Age” and “Distance.”
c. Based on the above parts, what value do you expect r to be? _________________________
d. The equation for the line of best fit is y = −3.0x + 576.7, which is included on the graph. Approximately what distance in feet would you expect a 50-year old driver to see?
e. Would it be appropriate to use our line of best fit to make a prediction about the distance seen by a 110 year old? ____________________ Doing so would be an example of what statistical concept? __________________________
Transcribed Image Text:Distance
700
600
500
400
300
200
100
0
10
20
Age vs. Distance
30
40
Age
50
60
70
80
90
Definition Definition Statistical measure used to assess the strength and direction of relationships between two variables. Correlation coefficients range between -1 and 1. A coefficient value of 0 indicates that there is no relationship between the variables, whereas a -1 or 1 indicates that there is a perfect negative or positive correlation.
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