Objective 3.2 Preprocess Data CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   What is the primary risk of removing rows with missing values?

   • ALosing a significant amount of data and potentially introducing bias
   • BCausing the dataset to become too large
   • CMaking the data more difficult to visualize
   • DIncreasing the number of features in the dataset
   Reveal Solution Discussion Select an answer first
2. 22application · medium

   A data scientist is preparing features for a support vector machine (SVM) with an RBF kernel. The feature 'salary' has a wide range and contains some outliers. The data scientist wants to scale the feature so that the SVM is not dominated by the large values. The data scientist also wants to preserve the relative distances between points as much as possible. What should the data scientist do?

   • ADo not scale the feature.
   • BApply min-max scaling.
   • CApply robust scaling.
   • DApply standardization (z-score).
   Reveal Solution Discussion Select an answer first
4. 23application · medium

   A data scientist is cleaning a customer churn dataset. The column 'income' has missing values. Analysis shows that the probability of 'income' being missing is higher for customers who have churned. The churn status is fully observed. The data scientist wants to handle the missing values in a way that minimizes bias in the churn prediction model. What should the data scientist do?

   • AReplace missing income with the mode income.
   • BImpute income with the overall mean income.
   • CDelete all rows with missing income values.
   • DImpute income using a model that includes churn status as a predictor.
   Reveal Solution Discussion Select an answer first
5. 24foundation · easy

   Which imputation method uses other features in the dataset to predict missing values?

   • AMedian imputation
   • BMode imputation
   • CModel-based imputation
   • DMean imputation
   Reveal Solution Discussion Select an answer first
6. 25foundation · easy

   Which formula is used for z-score standardization?

   • A(x - median) / interquartile range
   • B(x - min) / (max - min)
   • C(x - mean) / standard deviation
   • Dx / max(x)
   Reveal Solution Discussion Select an answer first