WGU D425 MIDTERM EXAM
QUESTIONS WITH VERIFIED ANSWERS
2026/2027.
1. Which phase of the CRISP-DM process model involves selecting the analytical technique
and calibrating parameters to optimal values?
A. Modeling
B. Data Preparation
C. Business Understanding
D. Evaluation
Answer: A
Conceptual Explanation: The Modeling phase focuses on selecting and applying various
techniques, such as regression or classification algorithms, and tuning their parameters.
2. Which level of measurement is characterized by having an absolute zero point, allowing for
the calculation of ratios?
A. Ordinal
B. Interval
C. Nominal
D. Ratio
,Answer: D
Conceptual Explanation: Ratio data has all the properties of interval data plus a definitive
zero point, meaning that ‘zero’ indicates the absence of the measured quantity.
3. In the context of the Big Data 4Vs, which ‘V’ refers to the uncertainty or unreliability of
data?
A. Veracity
B. Volume
C. Velocity
D. Variety
Answer: A
Conceptual Explanation: Veracity refers to the quality, accuracy, and trustworthiness of
the data.
4. What is the primary objective of ‘Data Wrangling’ in the data lifecycle?
A. Archiving data for long-term storage
B. Visualizing data for stakeholders
C. Collecting data from primary sources
D. Cleaning and transforming raw data into a usable format
Answer: D
, Conceptual Explanation: Data wrangling (or munging) involves cleaning, structuring, and
enriching raw data into a format suitable for analysis.
5. Which statistical measure is most sensitive to extreme outliers in a dataset?
A. Median
B. Mode
C. Mean
D. Interquartile Range
Answer: C
Conceptual Explanation: The mean is calculated by summing all values; therefore, one
very large or small value can significantly pull the average away from the center.
6. Which type of machine learning uses labeled datasets to train algorithms to classify data or
predict outcomes?
A. Unsupervised Learning
B. Reinforcement Learning
C. Semi-supervised Learning
D. Supervised Learning
Answer: D
Conceptual Explanation: Supervised learning requires input-output pairs (labels) to learn
a mapping function from the input to the output.
QUESTIONS WITH VERIFIED ANSWERS
2026/2027.
1. Which phase of the CRISP-DM process model involves selecting the analytical technique
and calibrating parameters to optimal values?
A. Modeling
B. Data Preparation
C. Business Understanding
D. Evaluation
Answer: A
Conceptual Explanation: The Modeling phase focuses on selecting and applying various
techniques, such as regression or classification algorithms, and tuning their parameters.
2. Which level of measurement is characterized by having an absolute zero point, allowing for
the calculation of ratios?
A. Ordinal
B. Interval
C. Nominal
D. Ratio
,Answer: D
Conceptual Explanation: Ratio data has all the properties of interval data plus a definitive
zero point, meaning that ‘zero’ indicates the absence of the measured quantity.
3. In the context of the Big Data 4Vs, which ‘V’ refers to the uncertainty or unreliability of
data?
A. Veracity
B. Volume
C. Velocity
D. Variety
Answer: A
Conceptual Explanation: Veracity refers to the quality, accuracy, and trustworthiness of
the data.
4. What is the primary objective of ‘Data Wrangling’ in the data lifecycle?
A. Archiving data for long-term storage
B. Visualizing data for stakeholders
C. Collecting data from primary sources
D. Cleaning and transforming raw data into a usable format
Answer: D
, Conceptual Explanation: Data wrangling (or munging) involves cleaning, structuring, and
enriching raw data into a format suitable for analysis.
5. Which statistical measure is most sensitive to extreme outliers in a dataset?
A. Median
B. Mode
C. Mean
D. Interquartile Range
Answer: C
Conceptual Explanation: The mean is calculated by summing all values; therefore, one
very large or small value can significantly pull the average away from the center.
6. Which type of machine learning uses labeled datasets to train algorithms to classify data or
predict outcomes?
A. Unsupervised Learning
B. Reinforcement Learning
C. Semi-supervised Learning
D. Supervised Learning
Answer: D
Conceptual Explanation: Supervised learning requires input-output pairs (labels) to learn
a mapping function from the input to the output.
