DA0-002 Practice Test 44 — 15 Questions

Question 1

A scatter plot of advertising spend vs. revenue shows no clear correlation, but the analyst suspects a relationship exists. Which addition to the plot could help reveal a hidden trend?

Accepted Answer

Add a trendline. Adding a trendline (e.g., linear regression) can reveal underlying patterns in noisy scatter plot data, making it easier to see correlations that are not immediately obvious from the raw points alone. Other options like changing to a bar chart, increasing marker size, or removing data points would not help reveal a hidden trend and may obscure the data.

Answer

Change to a bar chart

Answer

Increase the marker size

Answer

Remove data points with low spend

Question 2

A financial institution is merging transaction data from two different systems. System A stores currency amounts as integers in cents, and System B stores as decimals in dollars. What is the best way to integrate the data?

Accepted Answer

Convert System A amounts to dollars by dividing by 100.. Converting System A's integer cents to dollars by dividing by 100 ensures both datasets share a consistent unit (dollars) and numeric data type (decimal). This direct transformation eliminates ambiguity in aggregation and reporting, as financial calculations require uniform precision and scale. Using a transformation layer or storing as strings would introduce unnecessary complexity or risk of rounding errors.

Answer

Keep both as is and use a transformation layer.

Answer

Store all amounts as strings to preserve precision.

Answer

Convert System B amounts to cents by multiplying by 100.

Question 3

A dataset contains outliers in a feature that will be used for linear regression. Which two outlier treatment methods are appropriate? (Choose TWO)

Accepted Answer

Cap the outliers at a percentile (e.g., 99th percentile). Capping outliers or transforming the variable can reduce their influence.

Answer

Use min-max normalization

Answer

Increase the sample size

Answer

Replace outliers with the mean

Question 4

Refer to the exhibit. A data analyst runs this query to identify high-value customers. However, the result does not include customers with exactly 5 orders. Which data concept does the HAVING clause illustrate?

Accepted Answer

Data aggregation with filtering on aggregated values. HAVING filters groups after aggregation, unlike WHERE which filters rows before aggregation. This demonstrates data aggregation with filtering on aggregated values.

Answer

Data sorting with ORDER BY

Answer

Data joining with INNER JOIN

Answer

Data filtering on row-level conditions

Question 5

A stakeholder asks for the exact number of customers who churned last month. Which metric should the analyst report?

Accepted Answer

Count of churned customers. The stakeholder explicitly asks for the 'exact number' of customers who churned, which is a discrete count. Option C, 'Count of churned customers,' directly provides this integer value without any normalization or ratio. The analyst should report the raw metric that matches the request's specificity.

Answer

Churn trend

Answer

Churn rate percentage

Answer

Churn probability

Question 6

Which THREE of the following are common mistakes when creating data visualizations? (Choose 3.)

Accepted Answer

Using a 3D pie chart. 3D pie charts distort the perception of proportions by adding a false depth dimension, making it difficult for viewers to accurately compare slice sizes. This violates the principle of data-ink ratio and is widely discouraged in data visualization best practices.

Answer

Choosing the correct chart type for the data

Answer

Labeling axes clearly

Question 7

Which TWO color choices are appropriate for a categorical data visualization? (Select two.)

Accepted Answer

Distinct hues. Distinct hues (A) are appropriate for categorical data because they use different colors to represent distinct categories without implying any order or magnitude. This aligns with best practices in data visualization where categorical variables require qualitative color schemes that maximize perceptual separation between groups.

Answer

Sequential color scheme

Answer

Monochrome

Answer

Rainbow gradient

Question 8

Which THREE characteristics describe unstructured data? (Select three.)

Accepted Answer

Contains text, images, audio, video. Unstructured data lacks a predefined data model and is typically composed of non-tabular formats such as text, images, audio, and video. Unlike structured data, it cannot be directly stored in relational databases without transformation. This characteristic is fundamental to distinguishing unstructured data from structured or semi-structured types.

Answer

Easily processed by standard SQL

Answer

Organised in rows and columns

Question 9

In A/B testing, the null hypothesis typically states that:

Accepted Answer

There is no difference between the control and treatment groups. The null hypothesis (H0) is a statement of no effect or no difference between groups.

Answer

The treatment group will perform better than the control group

Answer

The sample size is sufficient for the test

Answer

There is a significant difference between the control and treatment groups

Question 10

In time series analysis, which component represents regular patterns that repeat over fixed periods, such as daily or yearly?

Accepted Answer

Seasonality. Seasonality refers to patterns that repeat at regular intervals.

Answer

Trend

Answer

Cyclical

Answer

Irregular

Question 11

A data analyst wants to visualize the monthly sales trend for the past year. Which chart type is most appropriate?

Accepted Answer

Line chart. Line charts are best for showing trends over time.

Answer

Bar chart

Answer

Pie chart

Answer

Scatter plot

Question 12

Which THREE of the following are appropriate methods to handle outliers in a dataset?

Accepted Answer

Transforming the data using log transformation. Log transformation compresses the scale of data, reducing the impact of extreme values and making the distribution more symmetric. This is a standard technique for handling skewed data where outliers are present, as it preserves the relative order of observations while mitigating outlier influence.

Answer

Binning continuous variables

Answer

Imputing outliers with the mean

Question 13

In a simple linear regression model y = 2.5 + 1.2x, what is the predicted value of y when x = 10?

Accepted Answer

14.5. Plug x=10: y = 2.5 + 1.2*10 = 2.5 + 12 = 14.5.

Answer

12.0

Answer

13.7

Answer

10.0

Question 14

A retail company stores customer transaction data in a relational database. They want to analyze purchasing patterns over time. Which type of data structure best supports this analysis?

Accepted Answer

Relational table. A relational table is the correct choice because it organizes transaction data into structured rows and columns with defined schemas, enabling efficient SQL-based queries for time-series analysis (e.g., aggregating purchases by date, customer, or product). The relational model supports ACID transactions and joins across related tables (e.g., customers, products, transactions), which is essential for analyzing purchasing patterns over time while maintaining data integrity.

Answer

Graph database

Answer

Document store

Answer

Key-value store

Question 15

Which measure best describes the spread of the middle 50% of a dataset?

Accepted Answer

IQR. Interquartile range (IQR) is the range between Q1 and Q3, covering the middle 50%.

Answer

Range

Answer

Standard deviation

Answer

Variance