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MIS 660 Topic 7 DQ 1
Suppose you wanted to understand the
relationship between a customer’s yearly income (X) and the number of movies
(Y) the customer watched in a year. You then gather data on incomes and the
number of movies watched in a year. The range of incomes in your data set is
$5K to $150K. After fitting a simple linear model and performing all the
appropriate diagnostics, the model showed that, on average, for every $10K in
income, the customer watched 1.5 movies in the year. So, for example, if a
customer earned 60K in a year, he or she would be expected to watch nine movies
during the year. Now you want to apply this model to your very wealthy friend
who will earn $1 million in the next year. Is this an appropriate application
of your model? Why or why not? Provide specific examples to justify your
opinion.
MIS 660 Topic 7 DQ 2
If you regress daily high temperature (Y) on
the amount of ice cream sales (X), you will notice that there is a strong
positive correlation between the two. In other words, as daily ice cream sales
increase, the daily high temperature increases. This implies that if we knew
the amount of ice cream sales in a particular day, we could estimate, with a
high level of accuracy, the high temperature in that day. Does this mean that
if we wanted to increase the daily temperature, we need to sell more ice cream?
Explain why or why not?
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