DA0-002 Practice Test 10 — 10 Questions

Question 1

A data analyst runs the Python code shown. What is the result of executing this code?

Accepted Answer

It reads the data, adds a calculated column, and shows the first 5 rows. The code reads a CSV file into a pandas DataFrame, then creates a new column 'total' by summing columns 'col1' and 'col2'. Finally, `head()` returns the first 5 rows. Option A correctly describes this sequence of operations.

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It throws an error because 'total' column already exists

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It reads the data and displays all rows

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It reads the data and displays summary statistics

Question 2

After a marketing campaign, sales increased by 15%. The analyst wants to understand which customer segment contributed most to the increase. Which type of analysis is this?

Accepted Answer

Diagnostic analysis. Diagnostic analysis is used to understand the root cause of an event or change. In this scenario, the analyst already knows sales increased by 15% and wants to determine which customer segment drove that increase, which is a classic diagnostic question. This type of analysis goes beyond describing what happened to explain why it happened.

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Predictive analysis

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Prescriptive analysis

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Descriptive analysis

Question 3

A data analyst is analyzing survey responses where respondents rated satisfaction on a scale of 1-5. The analyst wants to visualize the distribution of responses. Which chart type is most appropriate?

Accepted Answer

Histogram. A histogram is the most appropriate chart for visualizing the distribution of a single discrete variable, such as satisfaction ratings on a 1-5 scale. It groups the responses into bins (each rating value) and displays the frequency of each bin using bars, clearly showing the shape, central tendency, and spread of the data.

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Box plot

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Scatter plot

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Line chart

Question 4

A data analyst is performing data cleaning. Which THREE steps are part of this process? (Choose three.)

Accepted Answer

Correcting inconsistent data. Correcting inconsistent data (Option A) is a core data cleaning step because it ensures that values follow a consistent format, such as standardizing date formats (e.g., 'MM/DD/YYYY' vs 'DD-MM-YYYY') or fixing capitalization (e.g., 'USA' vs 'usa'). This process directly addresses data quality issues that arise from human entry errors or system differences, making the dataset reliable for analysis.

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Normalization

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Feature engineering

Question 5

A data analyst at a marketing firm is creating a weekly performance report for the marketing team. The report includes metrics like click-through rates, conversion rates, and cost per acquisition. The team prefers a quick overview of the week's performance to identify trends and make decisions in their Monday morning meeting. The meeting is only 30 minutes, and the team has limited time to review data. The analyst wants to provide a report that is concise and actionable. What format should the analyst use?

Accepted Answer

A one-page executive summary with key metrics highlighted.. A one-page executive summary with key metrics highlighted provides the marketing team with a concise, actionable overview that can be quickly reviewed in a 30-minute meeting. This format aligns with the requirement for a quick overview to identify trends and make decisions without overwhelming the team with excessive detail or requiring interactive exploration.

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A live dashboard with interactive filters.

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A detailed spreadsheet with all data.

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A 20-slide presentation.

Question 6

A healthcare provider needs to integrate patient data from multiple clinics into a single data warehouse. Which process is used to extract, transform, and load the data?

Accepted Answer

ETL. ETL (Extract, Transform, Load) is the correct process because the healthcare provider must first extract data from multiple source clinics, then transform it (e.g., standardize formats, clean duplicates, apply business rules) before loading it into the target data warehouse. This ensures data quality and consistency, which is critical for clinical analytics and reporting.

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ELT

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OLAP

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OLTP

Question 7

A researcher wants to study the effect of a new drug. She collects data directly from clinical trial participants. Later, she compares her findings with historical data from medical journals. Which contrast best describes her data sources?

Accepted Answer

Primary vs. Secondary. The researcher is directly collecting data from clinical trial participants (primary data) and then comparing it with historical data from medical journals (secondary data). Primary data is original data collected firsthand for a specific purpose, while secondary data is pre-existing data collected by others for different purposes. This contrast directly maps to the primary vs. secondary data classification in data management.

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Internal vs. External

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Quantitative vs. Qualitative

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Structured vs. Unstructured

Question 8

A marketing analyst wants to segment customers based on their purchase history, including total spent, number of transactions, and average order value. The analyst runs k-means clustering with k=5 on the raw data but notices that the cluster assignments change significantly every time the algorithm is executed. What should the analyst do first to obtain consistent and meaningful clusters?

Accepted Answer

Normalize the features and set a fixed random seed for the initial centroids.. The instability in cluster assignments is caused by the algorithm's sensitivity to the scale of features and the random initialization of centroids. Normalizing the features ensures that each variable contributes equally to the distance calculations, while setting a fixed random seed makes the initial centroid selection deterministic, leading to reproducible results.

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Switch to hierarchical clustering, which does not require specifying k.

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Increase the number of clusters to k=10 to capture more detail.

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Use principal component analysis (PCA) to reduce the number of features to two.

Question 9

Refer to the exhibit. Which type of data is the field "region"?

Accepted Answer

Qualitative. The field 'region' contains categorical labels (e.g., 'North', 'South', 'East', 'West') that represent distinct groups or categories, not numerical measurements. Qualitative data (also called categorical data) describes attributes or characteristics that can be named but not meaningfully ordered or measured on a numeric scale. Since 'region' assigns a name to a geographic area without any inherent numeric value or order, it is a classic example of qualitative data.

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Continuous

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Quantitative

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Discrete

Question 10

A dataset has missing values in the 'age' column. The distribution of age is approximately normal with few outliers. Which imputation method is most appropriate?

Accepted Answer

Mean imputation. For normally distributed data, mean imputation is reasonable and preserves the mean.

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Forward-fill

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Delete all rows with missing data

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Mode imputation