DA0-002 Practice Test 32 — 15 Questions

Question 1

A data analyst is reviewing sales data and wants to find orders where the order total is between $100 and $500, inclusive. Which WHERE clause is correct?

Accepted Answer

total BETWEEN 100 AND 500. The BETWEEN operator is inclusive of both endpoints, so 'total BETWEEN 100 AND 500' returns rows where total is greater than or equal to 100 and less than or equal to 500 — exactly the inclusive range requested. It is equivalent to 'total >= 100 AND total <= 500' but more concise and readable.

Answer

total > 100 AND total < 500

Answer

total IN (100, 500)

Answer

total >= 100 OR total <= 500

Question 2

A data scientist is using K-means clustering with k=3. After the first iteration, the centroids are recalculated. Which step occurs next in the algorithm?

Accepted Answer

Assign each point to the nearest centroid. After centroids are recalculated, K-means returns to the assignment step, reassigning each data point to the nearest (typically Euclidean distance) centroid. This assignment-then-update loop repeats until convergence — either centroids stop moving, assignments stabilize, or a maximum iteration count is reached. So the next step after recalculation is reassignment.

Answer

Calculate the sum of squared errors

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Stop the algorithm because k is fixed

Answer

Compute the elbow curve

Question 3

Which chart type is best for visualizing the correlation between two continuous variables?

Accepted Answer

Scatter plot. A scatter plot places each observation as a point on a two-dimensional plane defined by the two continuous variables, making the strength, direction, and shape (linear vs. nonlinear) of their relationship directly visible. It is the standard chart for bivariate correlation analysis.

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Pie chart

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Bar chart

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Line chart

Question 4

A data analyst is working with a relational database that contains a table of customer orders. To optimize query performance for a report that filters by order date and customer ID, the analyst wants to create an index. Which type of index would be most effective for queries that filter on both columns?

Accepted Answer

Composite index on (order_date, customer_id). A composite B-tree index on (order_date, customer_id) allows the database to efficiently satisfy equality and range predicates on both columns in a single index scan. B-tree indexes support ordered traversal and range lookups, making them ideal for date-based filtering combined with an equality filter on customer_id. This index structure minimizes the number of rows scanned by leveraging the index's leading column for the date range and the second column for the customer ID match.

Answer

B-tree index on order_date

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Hash index on customer_id

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Clustered index on order_id

Question 5

A data analyst notices that the sales numbers in a report differ from the numbers in the finance department's spreadsheet. This discrepancy is most likely due to a lack of:

Accepted Answer

Single version of truth. A single version of truth means all departments use the same centralized data, avoiding inconsistencies.

Answer

Row-level security

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Data lineage

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Data dictionary

Question 6

A data analyst wants to show the correlation between advertising spend and website traffic. Which chart type should they use?

Accepted Answer

Scatter plot. A scatter plot displays each observation as a point with one variable on the x-axis (advertising spend) and another on the y-axis (website traffic), making the relationship, direction, and strength of correlation immediately visible. It's the standard chart for bivariate correlation analysis because it preserves individual data points rather than aggregating them.

Answer

Area chart

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Bar chart

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Line chart

Question 7

A data analyst calculates the mean, median, and mode of a dataset. Which of the following measures of central tendency is least affected by extreme outliers?

Accepted Answer

Median. The median is the middle value when data is ordered, so it depends only on the rank position of values, not their magnitude. Extreme outliers, even if arbitrarily large or small, do not change which value sits in the middle unless they cross the 50th percentile. This makes the median a robust measure of central tendency, unlike the mean, which incorporates every value and is pulled toward outliers.

Answer

Range

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Mode

Answer

Mean

Question 8

A data analyst needs to count the number of orders placed by each customer, but only for customers who have placed more than 5 orders. Which SQL clause should be used to filter the aggregated results?

Accepted Answer

HAVING. HAVING is used to filter groups after aggregation. The query would use GROUP BY customer_id, then HAVING COUNT(*) > 5.

Answer

FILTER

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WHERE

Answer

LIMIT

Question 9

Which THREE of the following are assumptions of linear regression? (Select THREE).

Accepted Answer

Independence of errors. Option C is correct because linear regression assumes the residuals (errors) are independent of one another, meaning there is no autocorrelation; violations such as serial correlation in time-series data bias standard errors. Option D is correct because homoscedasticity—constant variance of the error terms across all levels of the predictors—is a core Gauss-Markov assumption; heteroscedasticity makes ordinary least squares estimates inefficient and invalidates inference. Option E is correct because the model assumes a linear relationship between each independent variable and the dependent variable, so the expected value of the outcome is a linear function of the coefficients. Option A is not an assumption: normality applies to the error terms (and is only strictly needed for small-sample inference), not to the independent variables themselves. Option B is not an assumption but a problem to avoid—multicollinearity among predictors inflates coefficient variances and should be absent, not assumed.

Answer

Normal distribution of independent variables

Answer

Multicollinearity among independent variables

Question 10

A data analyst is performing a hypothesis test with a significance level of 0.05. The p-value obtained is 0.03. What should the analyst conclude?

Accepted Answer

Reject the null hypothesis. Since the p-value (0.03) is less than the significance level (0.05), the result is statistically significant. This means the observed data provides sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis. The analyst should conclude that there is a statistically significant effect or difference.

Answer

Fail to reject the null hypothesis

Answer

Accept the null hypothesis

Answer

The result is practically significant

Question 11

When presenting data insights, which three practices help ensure clarity? (Choose THREE.)

Accepted Answer

Use consistent color coding. Option C is correct because consistent color coding lets viewers instantly associate a color with the same category, metric, or series across every chart, slide, or dashboard, reducing cognitive load and preventing misinterpretation. Option D is correct because clearly labeling axes—including units, scale, and time period—ensures the audience knows exactly what is being measured and how to read the values, which is essential for accurate interpretation. Option E is correct because providing context and benchmarks (such as targets, prior-period comparisons, or industry averages) turns raw numbers into meaningful insights and helps the audience judge whether a result is good, bad, or expected. Option A does not belong because including every data point creates clutter and obscures the key message; effective visualizations simplify and highlight what matters. Option B does not belong because overlaying multiple chart types on a single axis is confusing and can distort scale relationships, so dual axes or separate charts are preferred when different measures must be shown.

Answer

Include all data points in the chart

Answer

Overlay multiple chart types on one axis

Question 12

In a dataset with variables on different scales (e.g., age in years and income in dollars), which preprocessing step is necessary before applying k-means clustering?

Accepted Answer

Normalization (scaling). K-means clustering relies on Euclidean distance to measure similarity between data points. When variables like age (in years) and income (in dollars) are on different scales, the variable with larger numeric values (income) will dominate the distance calculation, skewing the clustering results. Normalization (scaling), such as min-max scaling or z-score standardization, rescales all features to a comparable range (e.g., [0,1] or mean=0, variance=1), ensuring each feature contributes equally to the distance computation.

Answer

Feature selection

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Dimensionality reduction

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One-hot encoding

Question 13

A data scientist is building a predictive model to forecast monthly sales. The data shows a linear trend with no seasonality. Which regression technique is most appropriate?

Accepted Answer

Linear regression. Linear regression is the most appropriate technique because the data shows a linear trend with no seasonality, making a straight-line model the simplest and most effective fit. It directly models the relationship between the independent variable (e.g., time) and the dependent variable (monthly sales) using a linear equation, minimizing the sum of squared residuals.

Answer

Polynomial regression

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Logistic regression

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Ridge regression

Question 14

Based on the exhibit, what is the most likely cause of the import failure?

Accepted Answer

A data quality issue: the date field contains an invalid date.. The exhibit shows a date field containing '2023-02-30', which is an invalid date (February never has 30 days). This data quality issue causes the import to fail, as the system likely validates date values against calendar rules before inserting them into the target table. The error is not due to file emptiness, non-numeric characters, or corruption, but specifically a semantic data integrity violation.

Answer

The file is empty or contains only headers.

Answer

The price field includes non-numeric characters that cannot be parsed.

Answer

The source file is corrupted or in an unsupported format.

Question 15

A data analyst discovers that the sales data for the current quarter shows a 15% increase in revenue. However, the analyst notes that the data does not include returns from the last week due to a system lag. How should the analyst communicate this uncertainty?

Accepted Answer

Include a caveat that returns from the last week are missing and revenue may be overstated.. The analyst must be transparent about the data's limitations. Since the missing returns could reduce the reported revenue increase, the correct action is to explicitly state that returns from the last week are not included and that the 15% figure may be overstated. This maintains data integrity and allows stakeholders to make informed decisions.

Answer

Delay the report until returns are processed.

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Report the 15% increase as final, because the returns are insignificant.

Answer

State that the revenue increase is exactly 15% and provide a confidence interval.