Objective 3.1 Examine Data CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 2)

Questions 6–10

1. 6expert · medium

   A data scientist is analyzing the relationship between 'age' and 'income'. The scatter plot shows a non-linear, monotonic increasing relationship. The Pearson correlation is 0.6, and the Spearman correlation is 0.9. Which correlation coefficient should be reported to accurately reflect the strength of the relationship?

   • ABoth, but report the average (0.75).
   • BSpearman (0.9), because it captures the monotonic relationship regardless of linearity.
   • CNeither, because the relationship is not linear.
   • DPearson (0.6), because it is the standard measure.
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2. 7application · easy

   A data scientist is examining the distribution of 'delivery_time' for an e-commerce company. A histogram shows the data is heavily concentrated around 3 days, but there is a long tail extending to 15 days. Which visualization would best help identify the outliers in this distribution?

   • AA histogram with more bins.
   • BA box plot of delivery_time.
   • CA bar chart of delivery_time categories.
   • DA scatter plot of delivery_time vs. order_id.
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4. 8foundation · easy

   A Pearson correlation coefficient of -0.85 between two variables indicates what?

   • AA weak negative linear relationship
   • BA strong positive linear relationship
   • CNo relationship between the variables
   • DA strong negative linear relationship
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5. 9application · medium

   A data scientist has a dataset with 10 numerical features and wants to quickly identify which pairs of features show strong linear relationships before building a regression model. Which visualization approach is most efficient for this initial screening?

   • ACreate individual histograms for each feature to understand their distributions.
   • BPlot a single scatter plot of the first two features only.
   • CUse a box plot for each feature to compare their ranges.
   • DGenerate a pair plot (scatterplot matrix) of all features to visually inspect pairwise relationships.
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6. 10application · medium

   A data scientist is preparing a dataset for a churn prediction model. The dataset includes 'customer_id', 'age', 'plan_type' (Basic/Standard/Premium), 'monthly_charges', and 'churned' (Yes/No). Which features are ordinal categorical?

   • Achurned and plan_type
   • Bplan_type
   • Cmonthly_charges and age
   • Dcustomer_id and age
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