DA0-002 Practice Test 42 — 15 Questions

Question 1

A sales dashboard shows monthly revenue but the bars are very tall for some months and very short for others, making comparisons difficult. Which visualization modification would best improve readability?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Apply a logarithmic scale on the y-axis. A logarithmic scale compresses the y-axis so that large values are displayed proportionally to small values, making it easier to compare relative changes across months with vastly different revenue figures. This is particularly useful when the data spans several orders of magnitude, as it prevents tall bars from dominating the view and short bars from being barely visible.

Answer

Change bar colors to gradient

Answer

Add more horizontal gridlines

Answer

Use a 3D bar chart for depth

Question 2

An analyst creates a bar chart showing average sales by region. They want to ensure that the y-axis starts at zero to avoid misleading interpretation. This practice aligns with which dashboard design principle?

Accepted Answer

Appropriate precision. Starting the y-axis at zero is a fundamental practice to ensure that the visual representation of data (bar heights) accurately reflects the actual values, preventing exaggeration or minimization of differences. This principle directly supports 'Appropriate Precision' by maintaining the integrity of the data visualization and avoiding misleading interpretations, which is a key consideration in dashboard design.

Answer

Visual hierarchy

Answer

Clear labels and titles

Answer

Data-ink ratio

Question 3

A data analyst needs to sample 1000 customers from a database of 100,000 customers for a survey, ensuring every customer has an equal chance of selection. Which sampling method is most appropriate?

Accepted Answer

Simple random sampling. Simple random sampling gives each individual an equal chance of being selected.

Answer

Cluster sampling

Answer

Stratified sampling

Answer

Systematic sampling

Question 4

A data analyst is using pandas in Python to clean a dataset. Which method is most appropriate to replace missing numerical values with the median of the column?

Accepted Answer

df.fillna(df.median()). fillna with median replaces missing values with median.

Answer

df.interpolate()

Answer

df.dropna()

Answer

df.replace(np.nan, df.mean())

Question 5

A data team is communicating findings from a machine learning model that predicts equipment failure. The model has high accuracy but low recall. Which of the following statements is the most accurate way to communicate the model's performance to the maintenance team?

Accepted Answer

"The model has a high precision but low recall, so it misses many failures.". It directly states that the model has high precision but low recall, which means that when the model predicts a failure, it is likely correct (few false positives), but it fails to identify many actual failures (many false negatives). This is the most accurate way to communicate the trade-off to the maintenance team, as it clearly indicates that the model will miss some failures despite its high accuracy.

Answer

"The model has a high precision, so when it alerts, it is usually correct, but it may miss some failures."

Answer

"The model rarely misses a failure, but may have false positives."

Answer

"The model is highly reliable and catches almost all failures."

Question 6

A data analyst is investigating a correlation between two continuous variables. Which THREE of the following are appropriate steps in this exploratory data analysis? (Select THREE.)

Accepted Answer

Calculate the Pearson correlation coefficient. Scatter plot visualizes relationship, correlation coefficient quantifies strength, and removing outliers may be needed to avoid misleading results.

Answer

Perform a t-test

Answer

Create a contingency table

Question 7

An analyst needs to compute a running total of sales for each department, ordered by date. Which window function is most appropriate?

Accepted Answer

SUM(sales) OVER (PARTITION BY department ORDER BY date). SUM() with OVER(PARTITION BY department ORDER BY date) computes a running total within each department.

Answer

ROW_NUMBER() OVER (PARTITION BY department ORDER BY date)

Answer

SUM(sales) OVER (ORDER BY date)

Answer

LAG(sales, 1) OVER (PARTITION BY department ORDER BY date)

Question 8

An analyst needs to show the part-to-whole relationship of market share among four competitors. Which chart type is most appropriate, considering best practices?

Accepted Answer

Pie chart. A pie or donut chart is suitable for part-to-whole with few categories (5-7 slices max). Here, four competitors fit well.

Answer

Scatter plot

Answer

Histogram

Answer

Box plot

Question 9

A data analyst wants to combine first_name and last_name columns into a single full_name column in a SQL query. Which string function should be used?

Accepted Answer

CONCAT(). CONCAT() joins two or more strings together.

Answer

UPPER()

Answer

LENGTH()

Answer

SUBSTRING()

Question 10

In an A/B test, the null hypothesis states that there is no difference between the conversion rates of the control and treatment groups. After collecting data, the p-value is 0.03. Using a significance level α = 0.05, what should the analyst conclude?

Accepted Answer

Reject the null hypothesis; there is a significant difference. Since the p-value (0.03) is less than α (0.05), the null hypothesis is rejected, indicating a statistically significant difference between the groups.

Answer

Accept the alternative hypothesis; the treatment is better

Answer

The test is inconclusive

Answer

Fail to reject the null hypothesis; no significant difference

Question 11

A data analyst is preparing to run an A/B test comparing two email subject lines. Which TWO of the following should the analyst define before the test begins?

Accepted Answer

The null and alternative hypotheses. Before A/B testing, define null and alternative hypotheses, and determine sample size needed for desired statistical power and effect size.

Answer

The exact lift in conversion rate

Answer

The time series decomposition

Answer

The p-value after the test

Question 12

A data analyst is testing whether the average sales amount differs between two regions. Which statistical test is most appropriate?

Accepted Answer

Two-sample t-test. A two-sample t-test compares the means of two independent groups.

Answer

Chi-square test

Answer

ANOVA

Answer

Paired t-test

Question 13

An analyst is conducting an A/B test on a new checkout process. To calculate sample size, which THREE factors must be considered?

Accepted Answer

Desired effect size. Statistical power, significance level (alpha), and desired effect size (minimum detectable effect) are essential for sample size calculation.

Answer

Number of control groups

Answer

Population standard deviation

Question 14

A data scientist is performing K-means clustering on customer data. She plots the within-cluster sum of squares (WCSS) for different values of k and observes an 'elbow' at k=4. What does this indicate?

Accepted Answer

The optimal number of clusters is 4. The elbow method suggests that adding more clusters beyond k=4 yields diminishing returns, so k=4 is a suitable number of clusters.

Answer

The algorithm should be run with k=3 to avoid overfitting

Answer

The data contains exactly 4 outliers

Answer

The WCSS is minimized at k=4, indicating perfect clustering

Question 15

A data analyst wants to compare the means of three different training methods on employee productivity. Which statistical test is most appropriate?

Accepted Answer

ANOVA. ANOVA (Analysis of Variance) is used to compare means of three or more groups.

Answer

Correlation analysis

Answer

Chi-square test

Answer

t-test