(1) An online retailer must decide whether to display advertisement A or advertisement B to each customer on the basis of collected customer demographics (age, income, zip code, and gender). A set of 150 of its customers have already expressed a preference for one advertisement or the other. (2) A policy analyst is interested in discovering factors that are associated with the crime rate across different U.S. cities. For each of 500 cities, the policy analyst gathers the following data: the crime rate, unemployment rate, population, median income, median home price, and state. (3) The the channel owner to see where the subscribers are located, their age and gender, the times and days they most ofte watch videos, and the subscription sources. SOE wishes to understand the different subtypes of subscribers. Engineering YouTube channel has 361 subscribers. YouTube allows

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Explain whether each scenario below is a regression, classification, or unsupervised learn-
ing problem. If it is a supervised learning scenario, indicate whether we are more interested
in inference or prediction. Finally, provide in each case the number of observations, n,
and the number of predictors, p.
(1) An online retailer must decide whether to display advertisement A or advertisement
B to each customer on the basis of collected customer demographics (age, income,
zip code, and gender). A set of 150 of its customers have already expressed a
preference for one advertisement or the other.
(2) A policy analyst is interested in discovering factors that are associated with the
crime rate across different U.S. cities. For each of 500 cities, the policy analyst
gathers the following data: the crime rate, unemployment rate, population, median
income, median home price, and state.
(3) The
the channel owner to see where the subscribers are located, their age and gender, the
times and days they most often watch videos, and the subscription sources. SOE
wishes to understand the different subtypes of subscribers.
Engineering YouTube channel has 361 subscribers. YouTube allows
Transcribed Image Text:Explain whether each scenario below is a regression, classification, or unsupervised learn- ing problem. If it is a supervised learning scenario, indicate whether we are more interested in inference or prediction. Finally, provide in each case the number of observations, n, and the number of predictors, p. (1) An online retailer must decide whether to display advertisement A or advertisement B to each customer on the basis of collected customer demographics (age, income, zip code, and gender). A set of 150 of its customers have already expressed a preference for one advertisement or the other. (2) A policy analyst is interested in discovering factors that are associated with the crime rate across different U.S. cities. For each of 500 cities, the policy analyst gathers the following data: the crime rate, unemployment rate, population, median income, median home price, and state. (3) The the channel owner to see where the subscribers are located, their age and gender, the times and days they most often watch videos, and the subscription sources. SOE wishes to understand the different subtypes of subscribers. Engineering YouTube channel has 361 subscribers. YouTube allows
Expert Solution
Step 1

Answer:- 

1)Classification problem. Here, we are more interested in prediction because the retailer wants to decide whether to display ad A or B to each customer. No. of observation n=150; no. of predictors=4 (age, income, zip code,  gender).

2)Since, the rate is to be determined which takes a numeric range not discrete values this is a regression problem. N=500, p=6

Here, we are more interested in inference rather than prediction. 

 

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