d. = 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. e. Interpret 2: (Round to two decimal places) There is a 77% 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. Given any group that spends a fixed amount of time at the store, 77% of all of those customers will spend the predicted amount of money at the store. 77% 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 77%. f. The equation of the linear regression line is: = (Please show your answers to two decimal places) g. 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.) h. Interpret the slope of the regression line in the context of the question: For every additional minute customers spend at the store, they tend to spend on averge $4.04 more money at the store. The slope has no practical meaning since you cannot predict what any individual customer will spend. As x goes up, y goes up. 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 $-6.51. 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 $-6.51. The average amount of money spent is predicted to be $-6.51.