A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 25 14 14 24 11 5 29 8 Money 105 70 78 92 33 18 103 55 r2r2 = (Round to two decimal places) Interpret r2r2 : 84% of all customers will spend the average amount of money at the store. Given any group that spends a fixed amount of time at the store, 84% of all of those customers will spend the predicted amount of money at the store. There is a 84% chance that the regression line will be a good predictor for the amount of money spent at the store based on the time spent at the store. There is a large variation in the amount of money that customers spend at the store, but if you only look at customers who spend a fixed amount of time at the store, this variation on average is reduced by 84%. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the amount of money spent by a customer who spends 14 minutes at the store. Dollars spent = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: As x goes up, y goes up. The slope has no practical meaning since you cannot predict what any individual customer will spend. For every additional minute customers spend at the store, they tend to spend on averge $3.35 more money at the store. Interpret the y-intercept in the context of the question: The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.75. The average amount of money spent is predicted to be $14.75. The y-intercept has no practical meaning for this study. If a customer spends no time at the store, then that customer will spend $14.75.

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 15PPS

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Question

A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below.

Time	25	14	14	24	11	5	29	8
Money	105	70	78	92	33	18	103	55

r2r2 = (Round to two decimal places)
Interpret r2r2 :
- 84% of all customers will spend the average amount of money at the store.
- Given any group that spends a fixed amount of time at the store, 84% of all of those customers will spend the predicted amount of money at the store.
- There is a 84% chance that the regression line will be a good predictor for the amount of money spent at the store based on the time spent at the store.
- There is a large variation in the amount of money that customers spend at the store, but if you only look at customers who spend a fixed amount of time at the store, this variation on average is reduced by 84%.
The equation of the linear regression line is:
ˆyy^ = + xx (Please show your answers to two decimal places)
Use the model to predict the amount of money spent by a customer who spends 14 minutes at the store.
Dollars spent = (Please round your answer to the nearest whole number.)
Interpret the slope of the regression line in the context of the question:
- As x goes up, y goes up.
- The slope has no practical meaning since you cannot predict what any individual customer will spend.
- For every additional minute customers spend at the store, they tend to spend on averge $3.35 more money at the store.
Interpret the y-intercept in the context of the question:
- The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.75.
- The average amount of money spent is predicted to be $14.75.
- The y-intercept has no practical meaning for this study.
- If a customer spends no time at the store, then that customer will spend $14.75.

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