A data analyst is exploring a dataset of customer ages. The analyst wants to check for data quality issues, specifically implausible values (e.g., negative ages or ages over 120). Which univariate EDA technique is most efficient for this task?

Create a scatter plot of age vs. customer ID

Count the number of unique values in the age column

Generate summary statistics (min, max, quartiles) and a histogram

Compute the mean and standard deviation only

A healthcare analyst is studying patient readmission rates. The dataset includes 'age', 'number_of_prior_visits', and 'readmitted' (yes/no). The analyst suspects that the relationship between age and readmission is not linear and may depend on the number of prior visits. Which EDA approach best reveals this potential interaction?

A correlation matrix of age, prior visits, and readmission (encoded as 0/1)

A single scatter plot of age vs. number of prior visits, colored by readmission status

Two separate histograms of age, one for readmitted and one for not readmitted

Faceted scatter plots of age vs. readmission rate, with one facet per quartile of prior visits

A data analyst is comparing the distribution of 'order_value' between two customer segments: 'new' and 'returning'. The 'new' segment has 10,000 customers, while the 'returning' segment has only 500. The analyst wants to compare the shapes of the two distributions fairly. Which visualization approach is most appropriate?

Two separate pie charts of order_value binned into ranges

A single bar chart of the total order_value for each segment

Overlaid histograms using raw counts

Overlaid histograms using probability density (normalized so each area sums to 1) instead of raw counts

A data scientist is exploring a dataset with three continuous variables: height, weight, and age. They want to visualize the pairwise relationships and also see the univariate distribution of each variable in a single figure. Which type of plot accomplishes this?

Three separate box plots, one for each variable

A 3D scatter plot of height, weight, and age

A single heatmap of the correlation matrix

A scatter plot matrix (pairplot) with histograms on the diagonal

CompTIADataX

Domain 2Objective 1

EDA Methods DY0-001 Practice Questions (Page 4)

Part of the Modeling, analysis, and outcomes domain, which accounts for 24% of the DY0-001 exam. CompTIA does not publish an official question count, but from its 165-minute exam (~65–110 total, ~16–26 in this domain), expect 3–5 from this objective — we provide 24 practice questions to prepare you well beyond it. (estimate)

24questions here

5free pages

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24%of the exam

Questions 16–20

16application · medium
A data analyst is exploring a dataset of customer ages. The analyst wants to check for data quality issues, specifically implausible values (e.g., negative ages or ages over 120). Which univariate EDA technique is most efficient for this task?
Select an answer first
17application · medium
A healthcare analyst is studying patient readmission rates. The dataset includes 'age', 'number_of_prior_visits', and 'readmitted' (yes/no). The analyst suspects that the relationship between age and readmission is not linear and may depend on the number of prior visits. Which EDA approach best reveals this potential interaction?
Select an answer first
18foundation · easy
Which visualization is specifically designed to show the distribution of a single continuous variable?
Select an answer first
19application · medium
A data analyst is comparing the distribution of 'order_value' between two customer segments: 'new' and 'returning'. The 'new' segment has 10,000 customers, while the 'returning' segment has only 500. The analyst wants to compare the shapes of the two distributions fairly. Which visualization approach is most appropriate?
Select an answer first
20application · medium
A data scientist is exploring a dataset with three continuous variables: height, weight, and age. They want to visualize the pairwise relationships and also see the univariate distribution of each variable in a single figure. Which type of plot accomplishes this?
Select an answer first

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EDA Methods DY0-001 Practice Questions (Page 4)

Questions 16–20

A data analyst is exploring a dataset of customer ages. The analyst wants to check for data quality issues, specifically implausible values (e.g., negative ages or ages over 120). Which univariate EDA technique is most efficient for this task?

Which visualization is specifically designed to show the distribution of a single continuous variable?

A data scientist is exploring a dataset with three continuous variables: height, weight, and age. They want to visualize the pairwise relationships and also see the univariate distribution of each variable in a single figure. Which type of plot accomplishes this?

Keep studying — Modeling, analysis, and outcomes