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More info Reign TV wants to start selling smart TVs and will only sell smart TVs to customers to whom they advertise. Managers use customer

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More info Reign TV wants to start selling smart TVs and will only sell smart TVs to customers to whom they advertise. Managers use customer information (income level, previous purchase history) to decide which customers they should target. The team needs to decide how sure it must be in predicting customer interest in a smart TV. If it is too cautious, it will choose a very high cutoff probability and only market to customers who it believes are very likely to be in the market for a smart TV. This may cause them to miss out on many customers. If they are too aggressive and choose a low cutoff probability, they may identify more individuals interested in buying smart TVs but also end up wasting marketing dollars on customers who are not interested in purchasing smart TVs. Data table Predicted Outcomes Buyers Non-Buyers Total Actual Buyers 6 30 Outcomes Non-Buyers 70 Total 32 100 Confusion Matrix (0.30) Predicted Outcomes Buyers Non-Buyers Total Actual Buyers 21 30 Outcomes Non-Buyers 70 Total 70 100Requirements 1. Complete the confusion matrices for the validation set. 2. A team of management accountants at Reign TV estimates the payoffs from their actions. For every customer it targets, Reign TV will spend $30 to market to that customer. For every smart TV it sells, Reign TV makes a prot of $230 after taking into account the S30 it spends on that customer. Construct the payoff matrix and determine which cut off value Reign TV should use. 3. Are there any other factors Reign TV should consider before building such a model? Reign TV sells TV sets. It does not sell smart TVs so customers do not some to Reign TV it they want to purchase smart TVs. 0 (Click the icon to View the additional information.) To choose a cutoff probability, the team develops the confusion matrices below for two cutoff probabilities on a validation sample of 100 households comprising 2 buyers and 70 non-buyers of smart TVs. (Click the icon to View the confusion matrices.) Read the m. Requirement 1. Complete the confusion matrices for the valldation set. Start by constructing a confusion matrix for the cutoff point 0.70. Confusion Matrix (0.70) Predicted Outcomes Buyers Non-Buyers Total Actual Buyers 6 30 Outcomes Non-Buyers 70 Total 32 100 Construct a confusion matrix for the cutoff point 0.30. Confusion Matrix (0.30) Predicted Outcomes Buyers Non-Buyers Total wuyVIV IVMI Actual Buyers 21 30 Outcomes Non-Buyers 70 Total 70 100 Requirement 2. A team of management accountants at Reign TV estimates the payoffs from their actions. For every customer it targets, Reign TV will spend $30 to market to that customer. For every smart TV it sells, Reign TV makes a profit of $230 after taking into account the $30 it spends on that customer. Construct the payoff matrix and determine which cut off value Reign TV should use. Start by constructing the payroll matrix. (Complete all answer boxes. Enter a 0 for any zero balances. Enter a spend or loss amount with a minus sign or parentheses.) Payoff Matrix Predicted Outcomes Buyers Non-Buyers Actual Buyers AnitaAMAR AlAM DINIAPPActual Buyers Outcomes Non-Buyers Calculate the payoff at each cutoff probability. Total payoff at cutoff 0.70 = Total payoff at cutoff 0.30 = Which cut off value should Reign TV use? Reign TV should use the cutoff value at V because it results in the V predicted payoff. Requirement 3. Are there any other factors Reign TV should consider before building such a model? [3. A. Reign TV should consider whether they could increase the Gini impurity of the data set used to make the prediction models. C: B. Reign TV should consider whether or not they could make their ROC curve less predictive. O C. Reign TV should consider the potential side effects of marketing too aggressively. If the company's marketing efforts irritate or offend interested customers, they may turn those customers away and lose sales. O D. No other factors need to be considered beyond those already analyzed when producing the prediction models discussed above

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