In simpler terms, the coefficient in a regression model shows the average change in the thing we're measuring (like revenue or bookings) when one thing, like PayDay, changes by one unit, assuming everything else stays the same. For example, if the PayDay coefficient is 96.68, it means that, on average, when it's a payday (going from 0 to 1), we see the target metric (like revenue or bookings) increase by 96.68 units, assuming nothing else changes. If I were talking to the operations team at Caesars, I would say: "Our model suggests that on paydays, we usually see an average increase of 96.68 units in our target metric. This could be because people have more money to spend on paydays. When planning our operations, we should keep this in mind, as we might expect more demand on these days." please rewrite and rephrase in most simple language and make it plagiarism-free In simpler terms, we wanted to see if Presidents Day has a big impact on the number of check-ins. The null hypothesis (Ho) said it doesn't, but the alternative hypothesis (H1) suggested it does. The data showed a clear effect - there's a 1303.94 percent increase in check-ins on Presidents Day because of the one-day extension. This means Presidents Day really matters for check-ins, and the numbers "t=8.06" and "p<0.05" tell us we can trust these findings. Explanation Solved by verified expert Ho: beta1 = 0 is the null hypothesis. President's Day does not have a statistically significant effect. H1 is an alternative hypothesis, which states that beta1 =/= 0. President Day has a statistically significant effect on the coefficient. The null hypothesis is rejected at the 5 percent level of significance with a t=8.06, p5 percent, and p5 percent. In this case, there is sufficient data to determine that the President Day coefficient is statistically significant. beta1 is equal to or equal to zero. There is a 1303.94 percent increase in check-ins on Presidents Day due to the one-day extension. " please rewrite and rephrase in simple language " please rewrite and rephrase in most simple language in 120 words Q-1 Interpret the coefficient Rate, -0.42. If you were part of the analytics team at Caesars, how would you explain this coefficient to the operations team