Vicki is in charge of the operations of Lyber, a ride-sharing start-up based in London. In order to understand what influences the demand Lyber faces, she asked Alan, her intern analyst, to conduct a regression analysis. The data Alan pulled out from the company's database is summarized in Table 3.1. The data includes the number of rides its customers requested (in the unit of 1,000 rides) in a day, the high temperature of the day (in Celsius), the price Lyber charges (pound per kilometre, /km), and whether the date recorded falls in a weekend or not (1 if weekend, 0 if not). The output of the first regression that Alan ran is exhibited in Table 3.2.

Table 3.1: Lyber Data

\fSUMMARY OUTPUT Regression Statistics Multiple R 0.910 R Square 0.827 Adjusted R Square 0.763 Standard Error 16.302 Observations 12 Coefficients Intercept 160.861 High Temperature 2.038 Price per km -84.034 Weekend? -24.358 Standard Error 34.942 0.820 23.379 10.417 t Stat 4.604 2.485 -3.594 -2.338 P-value 0.002 0.038 0.007 0.048 Lower 95% Upper 95% 80.283 0.146 -137.946 -48.380 241.438 3.929 -30.121 -0.337