Q And A For Final Module 1

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Question Description

Question 11 pts

SQL is an acronym for _____________.

Group of answer choicesSpeed Query Language

Special Query Language

Structured Query Language

Statistics Query Language

Flag this QuestionQuestion 21 pts

For a prediction task with 7 features, what would be a desirable sample size?

Group of answer choices70

50

35

7

Flag this QuestionQuestion 31 pts

The response (outcome) variable is whether the customer defaulted on their debt. The
predictor is the average balance and gender (gender = 1 if male and 0 if female). The following
R output is the fitted logistic regression model.

Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -10.87 0.5170250 -21.03 <2e-16 *** balance 0.001744 0.0002494 6.99 <2e-16 *** genderM -0.631 0.1153 -5.47 <2e-16 *** — From the output, will a male customer with the average debt of $4000 default?Group of answer choicesCannot determine since each customer is different. The customer is very unlikely to default. The customer is very likely to default. The customer will default. Flag this QuestionQuestion 41 pts Classification and Regression Trees (CART) is __________. Group of answer choicesa supervised learning technique to classify binary outcomes a supervised learning technique to classify the data value into a given category a supervised learning technique for classification that is based on tree-based None of these Flag this QuestionQuestion 51 pts k-nearest neighbor (kNN) is ______________. Group of answer choicesa supervised learning technique to classify binary outcomes a supervised learning technique to classify the data value into a given category a supervised learning technique for classification that is based on tree. None of these Flag this QuestionQuestion 61 pts Consider the dataset 1.3, 1.5, 2.6, 2.8, 3.3, 4.0, 8.9. Using a rule of +/-3, it 8.9 an outlier? The mean and standard deviation are 3.5 and 2.57, respectively. Group of answer choicesYes No Maybe Cannot be determined Flag this QuestionQuestion 71 pts Which one of the following is NOT a data mining algorithm after completion of sampling, handling missing values, and dealing with outliers? Group of answer choicesDimension reduction Imputation Feature representation Feature scaling Flag this QuestionQuestion 81 pts Consider the following dataset. Compute the distance between the 1st and 3rd sample. sampleaciditydensityalcoholpH100.99689.83.220.040.9979.83.2630.560.9989.83.16Group of answer choices0.110 0.315 0.561 0.735 Flag this QuestionQuestion 91 pts The response (outcome) variable is whether the customer defaulted on their debt. The predictor is the average balance. The following R output is the fitted logistic regression model. Coefficients: Estimate Std. Error z value Pr(>|z|)
(Intercept) -10.87 0.5170250 -10.08 <2e-16 *** balance 0.001744 0.0002494 11.12 <2e-16 *** — From the output, will a customer with the average debt of $8000 default?Group of answer choicesCannot determine since each customer is different. The customer is very unlikely to default. The customer is very likely to default. The customer will default. Flag this QuestionQuestion 101 pts Data mining is ____________. Group of answer choicesa domain-specific language in programming and it is designed to handle structured data the process of collecting, organizing, analyzing, interpreting and presenting the data the process of discovering patterns in large datasets to predict outcomes all of the above

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