DA0-002 Practice Test 23 — 15 Questions

Question 1

A retail company wants to identify customer segments based on purchase history and demographics. Which technique is most appropriate for this task?

Accepted Answer

K-means clustering. K-means clustering is an unsupervised learning technique designed to segment data into groups based on similarity.

Answer

Linear regression

Answer

Chi-square test

Answer

Logistic regression

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. In K-means, after recalculating centroids, each point is reassigned to the nearest centroid, then centroids are updated again, iterating until convergence.

Answer

Calculate the sum of squared errors

Answer

Stop the algorithm because k is fixed

Answer

Compute the elbow curve

Question 3

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

Accepted Answer

Scatter plot. Scatter plots are designed to show the relationship between two numerical variables.

Answer

Area chart

Answer

Bar chart

Answer

Line chart

Question 4

A sales manager wants to display the contribution of each product category to total revenue, with a maximum of six categories. Which chart type is most suitable?

Accepted Answer

Pie chart. A pie or donut chart is ideal for part-to-whole relationships with a limited number of categories (5-7 slices).

Answer

Histogram

Answer

Box plot

Answer

Scatter plot

Question 5

A dataset contains the ages of 100 customers. The analyst wants to transform the ages to a 0-1 range for use in a distance-based algorithm. Which technique should be used?

Accepted Answer

Min-max normalization. Min-max normalization scales features to a fixed range, typically 0-1.

Answer

Square root transformation

Answer

Log transformation

Answer

Z-score normalization

Question 6

A data analyst needs to visualize the distribution of customer ages in a dataset. The analyst wants to see the frequency of ages grouped into bins. Which chart type should be used?

Accepted Answer

Histogram. A histogram groups continuous data into bins and shows the frequency of each bin, making it ideal for visualizing the distribution of a continuous variable like age.

Answer

Pie chart

Answer

Box plot

Answer

Bar chart

Question 7

A data analyst needs to visualize the distribution of customer ages in a dataset containing 10,000 records. The analyst wants to see the shape of the distribution and identify any outliers. Which chart type is most appropriate?

Accepted Answer

Histogram. A histogram shows the distribution of a continuous variable and can reveal shape and outliers when bins are appropriately sized.

Answer

Line chart

Answer

Box plot

Answer

Pie chart

Question 8

A dataset contains employee salaries ranging from $30,000 to $200,000. An analyst wants to scale the salaries to a range of 0 to 1 for use in a distance-based clustering algorithm. Which method should they use?

Accepted Answer

Min-max normalization. Min-max normalization scales data to a 0-1 range.

Answer

Log transformation

Answer

Robust scaling

Answer

Z-score standardization

Question 9

A data analyst wants to understand the relationship between advertising spend and sales revenue. The analyst calculates a Pearson correlation coefficient of 0.85. Which of the following is the best interpretation?

Accepted Answer

There is a strong positive linear relationship between advertising spend and sales.. Pearson r ranges from -1 to +1; 0.85 indicates a strong positive linear relationship, but correlation does not imply causation.

Answer

85% of the variation in sales is explained by advertising spend.

Answer

Increasing advertising spend by $1 will increase sales by $0.85.

Answer

There is a strong negative linear relationship between advertising spend and sales.

Question 10

In Looker Studio, you have a data source with daily sales and a separate data source with marketing spend. You want to create a chart that shows sales and marketing spend on the same axis, but the two sources are not joined natively. Which feature should you use to combine them?

Accepted Answer

Data blending. Data blending in Looker Studio allows you to combine data from multiple sources based on a common dimension without requiring a native join.

Answer

Filters

Answer

Community connectors

Answer

Calculated fields

Question 11

In Tableau, an analyst wants to create a calculated field that returns the average sales per customer only for customers who have made more than five purchases. Which Tableau function or approach would be most efficient?

Accepted Answer

Use a Level of Detail expression to count purchases per customer, then filter. Level of Detail (LOD) expressions like { FIXED [Customer ID] : SUM(…) } allow computations at a granular level. Then using an IF condition on the LOD result filters to customers with >5 purchases.

Answer

Use a table calculation for running sum

Answer

Use a context filter on the number of records

Answer

Create a parameter to filter customers

Question 12

A data analyst wants to compare the total sales of four different product categories for a single year. Which chart type is most appropriate for this comparison?

Accepted Answer

Bar chart. A bar chart is ideal for comparing discrete categories because the length of each bar represents the total value, making it easy to see which category has the highest sales.

Answer

Pie chart

Answer

Scatter plot

Answer

Line chart

Question 13

Which data quality dimension ensures that data represents the real-world object or event correctly?

Accepted Answer

Accuracy. Accuracy refers to how well data reflects reality.

Answer

Completeness

Answer

Consistency

Answer

Timeliness

Question 14

A data analyst is performing time series analysis on monthly sales data and notices a consistent pattern of higher sales every December. Which component of time series does this represent?

Accepted Answer

Seasonality. Seasonality refers to regular patterns that repeat at fixed intervals, such as yearly.

Answer

Trend

Answer

Irregular component

Answer

Cyclical

Question 15

A dataset contains features with vastly different scales (e.g., age 0-100 and income 0-1,000,000). Which data transformation should be applied before using a K-nearest neighbors algorithm?

Accepted Answer

Min-max normalization. Distance-based algorithms like KNN require features on similar scales; min-max normalization is appropriate.

Answer

No transformation is needed

Answer

Log transformation

Answer

Z-score standardization