Q. 1
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
For a standard normal distribution Z ~ N(0, 1), the mean and variance are:
C
Mean = 0, Variance = 1
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Standardizing transforms any normal random variable X into Z with μ=0 and σ²=1.
Q. 2
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
Newton-Raphson iterative formula for solving non-linear equation f(x) = 0 is:
B
x_(n+1) = x_n - f(x_n) / f'(x_n)
✓ Correct
D
x_(n+1) = f'(x_n) / f(x_n)
💡
Step-by-Step Explanation & Concept Rationale
Uses tangent line linear approximation to converge quadratically to the root.
Q. 3
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
In hypothesis testing, a Type I error occurs when:
A
Sample size is too small
B
Failing to reject a false null hypothesis
C
Rejecting a true null hypothesis (False Positive)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Type I error probability is the significance level alpha (α), typically 0.05.
Q. 4
MULTIPLE_CHOICE
Difficulty: HARD
(1 Mark)
Trapezoidal rule approximates the definite integral ∫ from a to b of f(x) dx as:
B
(h / 2) * [f(a) + 2 f(x1) + ... + 2 f(x_(n-1)) + f(b)]
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Linear interpolation across sub-intervals yields composite trapezoidal quadrature.
Q. 5
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
The central limit theorem states that the sampling distribution of sample means approaches normal as sample size n grows:
A
Regardless of the underlying population distribution shape (for n ≥ 30)
✓ Correct
C
Only for uniform distributions
D
Only if population is already normal
💡
Step-by-Step Explanation & Concept Rationale
Fundamental statistical theorem enabling inferential parametric confidence intervals.
Q. 6
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
In professional practice: For a standard normal distribution Z ~ N(0, 1), the mean and variance are:
A
Mean = 0, Variance = 1
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Standardizing transforms any normal random variable X into Z with μ=0 and σ²=1.
Q. 7
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
In professional practice: Newton-Raphson iterative formula for solving non-linear equation f(x) = 0 is:
A
x_(n+1) = f'(x_n) / f(x_n)
B
x_(n+1) = x_n - f(x_n) / f'(x_n)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Uses tangent line linear approximation to converge quadratically to the root.
Q. 8
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
In professional practice: In hypothesis testing, a Type I error occurs when:
A
Sample size is too small
B
Failing to reject a false null hypothesis
C
Rejecting a true null hypothesis (False Positive)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Type I error probability is the significance level alpha (α), typically 0.05.
Q. 9
MULTIPLE_CHOICE
Difficulty: HARD
(1 Mark)
In professional practice: Trapezoidal rule approximates the definite integral ∫ from a to b of f(x) dx as:
D
(h / 2) * [f(a) + 2 f(x1) + ... + 2 f(x_(n-1)) + f(b)]
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Linear interpolation across sub-intervals yields composite trapezoidal quadrature.
Q. 10
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
In professional practice: The central limit theorem states that the sampling distribution of sample means approaches normal as sample size n grows:
B
Only if population is already normal
C
Only for uniform distributions
D
Regardless of the underlying population distribution shape (for n ≥ 30)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Fundamental statistical theorem enabling inferential parametric confidence intervals.
Q. 11
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
According to standard examination standards: For a standard normal distribution Z ~ N(0, 1), the mean and variance are:
D
Mean = 0, Variance = 1
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Standardizing transforms any normal random variable X into Z with μ=0 and σ²=1.
Q. 12
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
According to standard examination standards: Newton-Raphson iterative formula for solving non-linear equation f(x) = 0 is:
A
x_(n+1) = x_n - f(x_n) / f'(x_n)
✓ Correct
D
x_(n+1) = f'(x_n) / f(x_n)
💡
Step-by-Step Explanation & Concept Rationale
Uses tangent line linear approximation to converge quadratically to the root.
Q. 13
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
According to standard examination standards: In hypothesis testing, a Type I error occurs when:
A
Sample size is too small
B
Rejecting a true null hypothesis (False Positive)
✓ Correct
D
Failing to reject a false null hypothesis
💡
Step-by-Step Explanation & Concept Rationale
Type I error probability is the significance level alpha (α), typically 0.05.
Q. 14
MULTIPLE_CHOICE
Difficulty: HARD
(1 Mark)
According to standard examination standards: Trapezoidal rule approximates the definite integral ∫ from a to b of f(x) dx as:
D
(h / 2) * [f(a) + 2 f(x1) + ... + 2 f(x_(n-1)) + f(b)]
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Linear interpolation across sub-intervals yields composite trapezoidal quadrature.
Q. 15
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
According to standard examination standards: The central limit theorem states that the sampling distribution of sample means approaches normal as sample size n grows:
B
Only if population is already normal
C
Regardless of the underlying population distribution shape (for n ≥ 30)
✓ Correct
D
Only for uniform distributions
💡
Step-by-Step Explanation & Concept Rationale
Fundamental statistical theorem enabling inferential parametric confidence intervals.
Q. 16
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
From an applied perspective: For a standard normal distribution Z ~ N(0, 1), the mean and variance are:
D
Mean = 0, Variance = 1
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Standardizing transforms any normal random variable X into Z with μ=0 and σ²=1.
Q. 17
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
From an applied perspective: Newton-Raphson iterative formula for solving non-linear equation f(x) = 0 is:
A
x_(n+1) = x_n - f(x_n) / f'(x_n)
✓ Correct
C
x_(n+1) = f'(x_n) / f(x_n)
💡
Step-by-Step Explanation & Concept Rationale
Uses tangent line linear approximation to converge quadratically to the root.
Q. 18
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
From an applied perspective: In hypothesis testing, a Type I error occurs when:
A
Sample size is too small
C
Failing to reject a false null hypothesis
D
Rejecting a true null hypothesis (False Positive)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Type I error probability is the significance level alpha (α), typically 0.05.
Q. 19
MULTIPLE_CHOICE
Difficulty: HARD
(1 Mark)
From an applied perspective: Trapezoidal rule approximates the definite integral ∫ from a to b of f(x) dx as:
B
(h / 2) * [f(a) + 2 f(x1) + ... + 2 f(x_(n-1)) + f(b)]
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Linear interpolation across sub-intervals yields composite trapezoidal quadrature.
Q. 20
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
From an applied perspective: The central limit theorem states that the sampling distribution of sample means approaches normal as sample size n grows:
A
Only if population is already normal
C
Regardless of the underlying population distribution shape (for n ≥ 30)
✓ Correct
D
Only for uniform distributions
💡
Step-by-Step Explanation & Concept Rationale
Fundamental statistical theorem enabling inferential parametric confidence intervals.
Q. 21
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
Under standard operational protocols: For a standard normal distribution Z ~ N(0, 1), the mean and variance are:
D
Mean = 0, Variance = 1
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Standardizing transforms any normal random variable X into Z with μ=0 and σ²=1.
Q. 22
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
Under standard operational protocols: Newton-Raphson iterative formula for solving non-linear equation f(x) = 0 is:
A
x_(n+1) = x_n - f(x_n) / f'(x_n)
✓ Correct
C
x_(n+1) = f'(x_n) / f(x_n)
💡
Step-by-Step Explanation & Concept Rationale
Uses tangent line linear approximation to converge quadratically to the root.
Q. 23
MULTIPLE_CHOICE
Difficulty: MEDIUM
(1 Mark)
Under standard operational protocols: In hypothesis testing, a Type I error occurs when:
A
Sample size is too small
C
Failing to reject a false null hypothesis
D
Rejecting a true null hypothesis (False Positive)
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Type I error probability is the significance level alpha (α), typically 0.05.
Q. 24
MULTIPLE_CHOICE
Difficulty: HARD
(1 Mark)
Under standard operational protocols: Trapezoidal rule approximates the definite integral ∫ from a to b of f(x) dx as:
A
(h / 2) * [f(a) + 2 f(x1) + ... + 2 f(x_(n-1)) + f(b)]
✓ Correct
💡
Step-by-Step Explanation & Concept Rationale
Linear interpolation across sub-intervals yields composite trapezoidal quadrature.
Q. 25
MULTIPLE_CHOICE
Difficulty: EASY
(1 Mark)
Under standard operational protocols: The central limit theorem states that the sampling distribution of sample means approaches normal as sample size n grows:
A
Regardless of the underlying population distribution shape (for n ≥ 30)
✓ Correct
C
Only if population is already normal
D
Only for uniform distributions
💡
Step-by-Step Explanation & Concept Rationale
Fundamental statistical theorem enabling inferential parametric confidence intervals.
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