SAS Certified BI Content Developer for SAS 9 and Business Analytics Questions and Answer (Dumps and Practice Questions)

Question : Suppose you have made a model for the rating system, which rates between to stars.
And you calculated that RMSE value is 1.0 then which of the following is correct

1. It means that your predictions are on average one star off of what people really think
2. It means that your predictions are on average two star off of what people really think
3. It means that your predictions are on average three star off of what people really think
4. It means that your predictions are on average four star off of what people really think


Correct Answer : 1


Explanation:





Question : You are creating a regression model with the input income, education and current debt of a customer,
what could be the possible output from this model.

1. Customer fit as a good
2. Customer fit as acceptable or average category
3. expressed as a percent, that the customer will default on a loan
4. 1 and 3 are correct
5. 2 and 3 are correct

Correct Answer : 3


Explanation: Regression is the process of using several inputs to produce one or more outputs. For example The input might be the income, education and current debt of a customer. The output might be the probability, expressed as a percent that the customer will default on a loan. Contrast this to classification where the output is not a number, but a class.




Question : In which of the scenario you can use the regression to predict the values

1. Samsung can use it for mobile sales forecast
2. Mobile companies can use it to forecast manufacturing defects
3. Probability of the celebrity divorce
4. Only 1 and 2
5. All 1 , 2 and 3

Correct Answer : 5

Explanation: Regression is a tool which Companies may use this for things such as sales forecasts or forecasting manufacturing defects. Another creative example is predicting the probability of celebrity divorce.

Related Questions

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Question : Assume a $ cost for soliciting a non-responder and a $ profit for soliciting a responder.
The logistic regression model gives a probability score named P_R on a SAS data set called VALID. The VALID
data set contains the responder variable Pinch, a 1/0 variable coded as 1 for responder. Customers will
be solicited when their probability score is more than 0.05. Which SAS program computes the profit for
each customer in the data set VALID?


1. A
2. B
3. C
4. D


Question : In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

1. Training: 50% Validation: 0% Testing: 50%
2. Training: 100% Validation: 0% Testing: 0%
3. Training: 0% Validation: 100% Testing: 0%
4. Training: 50% Validation: 50% Testing: 0%




Question : Refer to the exhibit:
Based upon the comparative ROC plot for two competing models,
which is the champion model and why?

1. Candidate 1, because the area outside the curve is greater
2. Candidate 2, because the area under the curve is greater
3. Candidate 1, because it is closer to the diagonal reference curve
4. Candidate 2, because it shows less over fit than Candidate 1



Question : A marketing campaign will send brochures describing an expensive product to a set of customers.
The cost for mailing and production per customer is $50. The company makes $500 revenue for each sale.
What is the profit matrix for a typical person in the population?

1. A
2. B
3. C
4. D



Question : Select the correct statements from the below.
1. The sum of errors will be larger than mean absolute error if errors are positive
2. The mean absolute error will, be larger than the sum if errors are negative
3. The mean absolute error will, be smaller than the sum if errors are negative
4. RMSE will equal MAE if all errors are equally large
5. RMSE will be smaller if all errors are not equally large
6. RMSE will be larger if all errors are not equally large

1. 1,3,4,6
2. 1,2,4,6
3. 2,3,4,6
4. 2,3,5,6




Question : You are working in an ecommerce organization, where you are designing and evaluating a recommender system,
you need to select which of the following metric will always have the largest value?

1. Root Mean Square Error
2. Sum of Errors
3. Mean Absolute Error
4. Information is not good enough.