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d. ² = e. Interpret ²: (Round to two decimal places) Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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. f. The equation of the linear regression line is: y = (Please show your answers to two decimal places) g. Use the model to predict the amount of money spent by a customer who spends 17 minutes at the store. Dollars spent = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: O The slope has no practical meaning since you cannot predict what any individual customer will spend. As x goes up, y goes up. For every additional minute customers spend at the store, they tend to spend on averge $3.34 more money at the store. i. Interpret the y-intercept in the context of the question: If a customer spends no time at the store, then that customer will spend $14.52. The average amount of money spent is predicted to be $14.52. The y-intercept has no practical meaning for this study. The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.52.

d. ² = e. Interpret ²: (Round to two decimal places) Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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. f. The equation of the linear regression line is: y = (Please show your answers to two decimal places) g. Use the model to predict the amount of money spent by a customer who spends 17 minutes at the store. Dollars spent = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: O The slope has no practical meaning since you cannot predict what any individual customer will spend. As x goes up, y goes up. For every additional minute customers spend at the store, they tend to spend on averge $3.34 more money at the store. i. Interpret the y-intercept in the context of the question: If a customer spends no time at the store, then that customer will spend $14.52. The average amount of money spent is predicted to be $14.52. The y-intercept has no practical meaning for this study. The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.52.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Answer parts d through i
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 Money 18 30 84 106 9 17 23 23 12 22 11 52 88 103 103 35 65 45 a. Find the correlation coefficient: r = 0.84 b. The null and alternative hypotheses for correlation are: Ho: P = 0 H₁: pe #0 The p-value is: 0.0044 Round to 2 decimal places. (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. There is statistically insignificant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. d. ² = e. Interpret ²: O There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful. (Round to two decimal places) Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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.
Transcribed Image Text: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 Money 18 30 84 106 9 17 23 23 12 22 11 52 88 103 103 35 65 45 a. Find the correlation coefficient: r = 0.84 b. The null and alternative hypotheses for correlation are: Ho: P = 0 H₁: pe #0 The p-value is: 0.0044 Round to 2 decimal places. (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. There is statistically insignificant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. d. ² = e. Interpret ²: O There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful. (Round to two decimal places) Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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 statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. O There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful. (Round to two decimal places) d. 7² = e. Interpret 7²: Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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. f. The equation of the linear regression line is: y = (Please show your answers to two decimal places) g. Use the model to predict the amount of money spent by a customer who spends 17 minutes at the store. Dollars spent = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: The slope has no practical meaning since you cannot predict what any individual customer will spend. As x goes up, y goes up. For every additional minute customers spend at the store, they tend to spend on averge $3.34 more money at the store. i. Interpret the y-intercept in the context of the question: Olf a customer spends no time at the store, then that customer will spend $14.52. The average amount of money spent is predicted to be $14.52. O The y-intercept has no practical meaning for this study. O The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.52.
Transcribed Image Text:There is statistically significant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. O There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of money that they spend at the store. Thus, the regression line is useful. (Round to two decimal places) d. 7² = e. Interpret 7²: Given any group that spends a fixed amount of time at the store, 71% of all of those customers will spend the predicted amount of money at the store. 71% of all customers will spend the average amount of money 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 71%. There is a 71% 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. f. The equation of the linear regression line is: y = (Please show your answers to two decimal places) g. Use the model to predict the amount of money spent by a customer who spends 17 minutes at the store. Dollars spent = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: The slope has no practical meaning since you cannot predict what any individual customer will spend. As x goes up, y goes up. For every additional minute customers spend at the store, they tend to spend on averge $3.34 more money at the store. i. Interpret the y-intercept in the context of the question: Olf a customer spends no time at the store, then that customer will spend $14.52. The average amount of money spent is predicted to be $14.52. O The y-intercept has no practical meaning for this study. O The best prediction for a customer who doesn't spend any time at the store is that the customer will spend $14.52.
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