It has become common to find a convenience store that also sells gas. The accompanying data describe the sales over time at a franchise outlet of a major oil company. Each row summarizes sales for one day. This particular station sells gas, and it also has a convenience store and car wash. The column labeled Sales gives the dollar sales of the convenience store, and the column Volume gives the number of gallons of gas sold. Formulate the regression model with dollar sales as the response and number of gallons sold (in 100s) as the predictor. Sales (Dollars) Volume (100s of Gallons) 1759 28.92 2229 33.48 1851 30.26 2037 30.21 2348 34.91 2407 34.41 2025 32.35 2107 36.61 2283 35.17 2416 41.14 2500 37.5 2037 34.72 2224 32.18 3494 36.09 2159 30.33 2085 36.08 2565 32.51 1238 17.42 1970 28.72 2231 33.75 2222 29.97 1984 32.72 2067 31.82 2356 34.62 1902 31.26 2151 30.69 1814 35.3 1883 37.88 2042 31.22 2097 37.78 Copy-and-paste the above data into software of your choice. Run a regression analysis using y = sales and x = volume. What is the regression equation? (Round to the nearest whole number.) Sales = + x Volume. Find the value of the t-statistic for the hypothesis test of zero slope. What is the value of this t-statistic, rounded to the nearest tenth (1 decimal place)? t = What is the appropriate conclusion to the hypothesis test of zero slope? At the 5% significance level, the null hypothesis of zero slope. (Type the word reject or phrase fail to reject.) Using the regression equation, what is the predicted sales of a store selling x = 30 hundreds of gallons? Round to the nearest whole number. A store selling x = 30 hundreds of gallons has predicted sales of $