Recall your hypotheses about the impact of the independent variables on the number of daily check-ins. Are there any coefficient
s that surprise you or contradict your original hypotheses? Develop a possible explanation for why the estimated coefficients might make sense in the context of the problem. Do the coefficients for payday or any of the holidays surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for day of the week surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Do any of the coefficients for the number of rooms reserved on a given day to a particular type of guest (TotalRewards, SpecialEvent, VIP, FreeIndependent, Wholesale, Group) surprise you? What was your original hypothesis for those variables? Interpret the coefficients and explain why they support or contradict your intuition. Does the coefficient Rate surprise you? What was your original hypothesis for that variable? Interpret the coefficient and explain why it supports or contradicts your intuition.
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Answer:
the probability that the mean student loan debt for these people is between $31000 and $33000 is 0.1331
Step-by-step explanation:
Given that:
Mean = 30000
Standard deviation = 9000
sample size = 100
The probability that the mean student loan debt for these people is between $31000 and $33000 can be computed as:
From Z tables:
Therefore; the probability that the mean student loan debt for these people is between $31000 and $33000 is 0.1331