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Popular SDS Exams | SDS Exam Actual Questions

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DASCA Senior Data Scientist Sample Questions (Q71-Q76):

NEW QUESTION # 71
Bernoulli random variable is a type of:

A. Discrete random variable
B. Sometimes Discrete or sometimes Continuous random variable
C. Both A and B
D. Continuous random variable

Answer: A

Explanation:
A Bernoulli random variable is the simplest form of discrete random variable.
It can take only two values:
1 with probability p (success).
0 with probability (1 - p) (failure).
Since the outcomes are finite (binary), it is a discrete random variable.
Option B (Continuous): Incorrect, as continuous variables take values from an interval (e.g., real numbers).
Option C and D: Incorrect, as Bernoulli is always discrete, never continuous.
Thus, the correct answer is Option A (Discrete random variable).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Probability & Statistics for Data Science: Random Variables and Bernoulli Distribution.

NEW QUESTION # 72
In unsupervised learning, learning takes place by based on these deductions in input data and developing patterns:

A. Both A and B
B. None of the above
C. Detecting irregularities
D. Detecting regularities

Answer: A

Explanation:
Unsupervised learning is a machine learning approach where no labeled outputs are provided. The algorithm discovers patterns or structures directly from raw data.
Option A (Detecting regularities): Correct. Unsupervised learning identifies hidden structures such as clusters, associations, and dimensionality reductions (e.g., k-means clustering, PCA).
Option B (Detecting irregularities): Correct. Outlier detection is also a part of unsupervised learning, often used in anomaly detection (e.g., fraud detection, intrusion detection).
Option C: Correct, since unsupervised learning helps detect both regularities (clusters, groups) and irregularities (outliers, anomalies).
Thus, the correct answer is Option C (Both A and B).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Unsupervised Learning: Clustering, Anomaly Detection, and Pattern Discovery.

NEW QUESTION # 73
Which of the following is TRUE for Business Metamorphosis?

A. The Business Metamorphosis phase helps drive an organization's core business model through the analytic insights gathered as the organization traverses the Big Data Business Model Maturity Index
B. Business Metamorphosis exercise can uncover Big Data requirements around decisions, analytics and data sources that can be leveraged to transform or metamorphose your organization's business model
C. Both A and C
D. The Business Metamorphosis phase is where organizations integrate the insights that they captured about their customers' usage patterns, product performance behaviors, and overall market trends to transform their business models
E. All of the above

Answer: E

Explanation:
Business Metamorphosis is the most advanced phase in the Big Data Business Model Maturity Index (BDBMMI), where organizations fundamentally transform their business models through analytics-driven insights.
Option A: Correct. This phase helps organizations identify big data requirements related to decisions, analytics, and sources that drive business transformation.
Option B: Correct. Organizations integrate customer usage patterns, product behaviors, and market trends into their decision-making to redesign or innovate their business model.
Option C: Correct. Business Metamorphosis ensures that the core business model evolves continuously, guided by insights derived across maturity stages.
Since all are correct, the best answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: Big Data Business Model Maturity Index.

NEW QUESTION # 74
Which of the following is main Machine Learning Library in Python?

A. Scikit-learn
B. SciPy
C. None of the above
D. NumPy
E. Matplotlib

Answer: A

Explanation:
Python supports multiple libraries for scientific computing and data analysis, but the primary machine learning library is:
Scikit-learn (Option B): Provides a wide range of machine learning algorithms for classification, regression, clustering, model evaluation, and preprocessing. It is the core ML library in Python.
NumPy (Option A): Provides numerical computing and array operations, essential for ML but not a machine learning library itself.
Matplotlib (Option C): Used for data visualization.
SciPy (Option D): Supports scientific computing and numerical methods, not focused on ML models.
Therefore, the correct answer is Option B (Scikit-learn).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Python Libraries for Machine Learning.

NEW QUESTION # 75
Which of the following is correct for Markov chain?

A. Both A and B
B. Both B and C
C. A Markov chain is a sequence of random variables X1, X2
D. A Markov chain is the state of a system at sequential points in time
E. A Markov chain is a sequence of fixed variables X1, X2

Answer: B

Explanation:
A Markov chain is a stochastic process describing a sequence of possible events, where the probability of each event depends only on the state attained in the previous step (the Markov property).
Option A: Incorrect. The variables are random, not fixed.
Option B: Correct. Markov chains represent the state of a system at sequential time points.
Option C: Correct. A Markov chain is indeed a sequence of random variables {X1, X2, ...} that satisfy the Markov property.
Option D: Incorrect, since A is wrong.
Option E: Correct, because both B and C are valid.
Thus, the correct answer is Option E (Both B and C).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Probabilistic Models: Markov Chains.

NEW QUESTION # 76
......

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