Question 1201
The total sum of squares (SST) represents:
A. Explained variation in Y
B. Unexplained variation in Y
C. Total variation in Y around its mean
D. Variation in X
Check answer
Select an option first.
Correct answer: C — Total variation in Y around its mean
Explanation: ✔ Why correct: SST = Σ(Yᵢ − Ȳ)² measures total variation in the dependent variable.
Question 1202
The relationship SST = SSR + SSE means:
A. Total variation equals explained plus unexplained variation
B. Explained variation equals unexplained variation
C. Regression always explains 100% of variation
D. SSE must always be zero
Check answer
Select an option first.
Correct answer: A — Total variation equals explained plus unexplained variation
Explanation: ✔ Why correct: This is the fundamental decomposition of variance in regression.
Question 1203
The mean squared error (MSE) in simple regression is:
A. SSE divided by n
B. SSE divided by n − 2
C. SSR divided by n
D. SSR divided by n − 1
Check answer
Select an option first.
Correct answer: B — SSE divided by n − 2
Explanation: ✔ Why correct: In simple regression, degrees of freedom = n − 2, so MSE = SSE / (n − 2).
Question 1204
The mean square regression (MSR) in simple regression equals:
A. SSR
B. SSR divided by 1
C. SSE divided by n − 2
D. SST divided by n
Check answer
Select an option first.
Correct answer: B — SSR divided by 1
Explanation: ✔ Why correct: With one independent variable, MSR = SSR / 1 = SSR.
Question 1205
An indicator (dummy) variable in regression is:
A. A variable that takes any real value
B. A variable coded 1 when a condition holds and 0 otherwise
C. A variable used only in nonparametric tests
D. A variable that replaces the dependent variable
Check answer
Select an option first.
Correct answer: B — A variable coded 1 when a condition holds and 0 otherwise
Explanation: ✔ Why correct: Dummy variables encode categorical conditions as 0/1.
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Question 1206
The sum of squares regression (SSR) measures:
A. Variation in Y explained by X
B. Variation in Y unexplained by X
C. Total variation in Y
D. Variation in X explained by Y
Check answer
Select an option first.
Correct answer: A — Variation in Y explained by X
Explanation: ✔ Why correct: SSR = Σ(Ŷᵢ − Ȳ)² measures explained variation.
Question 1207
The sum of squared errors (SSE) measures:
A. Explained variation
B. Unexplained variation
C. Total variation
D. Variation in X
Check answer
Select an option first.
Correct answer: B — Unexplained variation
Explanation: ✔ Why correct: SSE = Σ(Yᵢ − Ŷᵢ)² measures residual (unexplained) variation.
Question 1208
Fintech refers to:
A. Any company that uses computers
B. Technology-driven innovation in financial services
C. Only blockchain-based financial applications
D. The regulation of financial markets
Check answer
Select an option first.
Correct answer: B — Technology-driven innovation in financial services
Explanation: ✔ Why correct: Fintech specifically refers to technological innovation in the design and delivery of financial services and products.
Question 1209
Big Data is characterized by the “3 Vs,” which include:
A. Volume, velocity, and validity
B. Volume, velocity, and variety
C. Variety, validity, and volatility
D. Velocity, volatility, and value
Check answer
Select an option first.
Correct answer: B — Volume, velocity, and variety
Explanation: ✔ Why correct: The classic Big Data definition includes volume, velocity, and variety.
Question 1210
Alternative data refers to:
A. Only traditional financial statements
B. Only government-released economic data
C. Non-traditional data sources such as social media and sensor networks
D. Data that has been manually collected by analysts
Check answer
Select an option first.
Correct answer: C — Non-traditional data sources such as social media and sensor networks
Explanation: ✔ Why correct: Alternative data includes non-traditional sources like social media, satellite images, sensors, and company exhaust.
Question 1211
Machine learning differs from traditional statistical methods because ML:
A. Requires strict assumptions about probability distributions
B. Learns patterns from data without explicit programming
C. Cannot be used for prediction
D. Only works with small datasets
Check answer
Select an option first.
Correct answer: B — Learns patterns from data without explicit programming
Explanation: ✔ Why correct: ML algorithms “learn” patterns from data and generalize without explicit human-written rules.
Question 1212
Unsupervised learning is most appropriate when:
A. The goal is to classify data into known categories
B. The data are labeled
C. The goal is to discover structure or groupings in unlabeled data
D. The model must predict future values
Check answer
Select an option first.
Correct answer: C — The goal is to discover structure or groupings in unlabeled data
Explanation: ✔ Why correct: Unsupervised learning identifies patterns, clusters, or structure in unlabeled data.
Question 1213
Deep learning differs from traditional ML because it:
A. Uses neural networks with multiple hidden layers to learn complex patterns
B. Requires no data
C. Only works with structured data
D. Cannot be used for supervised learning
Check answer
Select an option first.
Correct answer: A — Uses neural networks with multiple hidden layers to learn complex patterns
Explanation: ✔ Why correct: Deep learning uses multi-layer neural networks to capture complex, nonlinear relationships.
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