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ICAR AIEEA-PG Probability Distributions & Sampling Distributions: practice questions

ICAR AIEEA-PG - Group 07 Statistical Sciences (Master's admission and PG scholarship) · India · National Testing Agency for ICAR

Original practice questions written to the published syllabus · not past papers
7worked here, free
28written to this exam in this subject
8syllabus units

What this subject covers

Every standard distribution a statistician must recognise and derive from: discrete and continuous families, their relations and limiting forms, compound and truncated distributions, order statistics, the bivariate normal and the sampling distributions chi-square, t and F.

In the exams: AICE-JRF Ag Stat Unit 1 and Unit 2 'compound and truncated distribution, order statistics' (heavy); GATE ST distributions and order statistics (heavy); IIT JAM MS (heavy); UPSC ISS Statistics I (heavy)

What ICAR AIEEA-PG asks from it

ICAR AIEEA-PG Group 07, CUET-PG Statistics, SSC JSO and state statistical services

Binomial, Poisson and normal: mean, variance, mode, fitting to data, normal-area calculations and the chi-square, t and F tests that follow.

Where the 28 questions fall

How our questions for ICAR AIEEA-PG spread across the units of Probability Distributions & Sampling Distributions. Difficulty: 19 easy, 9 medium, 0 hard.

Discrete distributions: Bernoulli, binomial, Poisson, geometric, negative binomial, hypergeometric and multinomial6
Continuous distributions: uniform, normal, exponential, gamma, beta, Cauchy, Weibull, lognormal5
Pearsonian system and fitting of distributions to agricultural data5
Relations and limiting forms among distributions4
Sampling distributions: chi-square, t and F and their properties4
Bivariate normal: marginal and conditional distributions2
Compound, mixture and truncated distributions1
Distributions of quadratic forms in normal variables (Cochran's theorem)1

7 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Discrete distributions: Bernoulli, binomial, Poisson, geometric, negative binomial, hypergeometric and multinomial · easy

A binomial variable has mean 6 and variance 2.4. What is n?

  1. 25
  2. 10
  3. 6
  4. 15
Answer and working

B. 10

q = variance/mean = 2.4/6 = 0.4, so p = 0.6 and n = 6/0.6 = 10. 15 comes from taking p = 0.4 (confusing p with q); 6 confuses n with the mean.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

2 · Continuous distributions: uniform, normal, exponential, gamma, beta, Cauchy, Weibull, lognormal · easy

Wet-day rainfall X is gamma with shape 3 and rate 0.5 per mm, so f(x) ∝ x² e^(−0.5x). What is Var(X)?

  1. 0.75 mm²
  2. 1.5 mm²
  3. 12 mm²
  4. 6 mm²
Answer and working

C. 12 mm²

With rate β, mean = α/β = 6 mm and variance = α/β² = 3/0.25 = 12 mm². 6 is the mean; 0.75 = αβ² wrongly treats 0.5 as a scale parameter (a parameterisation slip).

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

3 · Continuous distributions: uniform, normal, exponential, gamma, beta, Cauchy, Weibull, lognormal · easy

X is uniform on (2, 8). What is Var(X)?

  1. 3
  2. 6
  3. 36
  4. 5
Answer and working

A. 3

Var = (b − a)²/12 = 36/12 = 3. 5 is the mean; 36 forgets to divide by 12.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

4 · Relations and limiting forms among distributions · easy

V has a chi-square distribution with 2 degrees of freedom. What is P(V > 6)?

  1. 0.000006
  2. 0.0498
  3. 0.0025
  4. 0.9502
Answer and working

B. 0.0498

χ²₂ is exponential with mean 2: P(V > 6) = e^(−6/2) = e^(−3) = 0.0498. e^(−6) treats the mean as 1.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

5 · Relations and limiting forms among distributions · medium

Calls to a farmers' helpline in a day are Poisson with mean 100. Using the normal approximation with continuity correction, what is P(at least 120 calls)?

  1. 0.0202
  2. 0.0256
  3. 0.4207
  4. 0.0228
Answer and working

B. 0.0256

Mean = variance = 100, SD 10. P(X ≥ 120) ≈ P(Z > (119.5 − 100)/10) = P(Z > 1.95) = 0.0256. Without correction z = 2 gives 0.0228; dividing by the variance gives z = 0.2.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

6 · Pearsonian system and fitting of distributions to agricultural data · medium

A binomial distribution is fitted to germination in 100 trays of 5 seeds, with an average of 4 seeds germinating per tray. What is the expected number of trays in which all 5 seeds germinate?

  1. 32.77
  2. 0.03
  3. 40.96
  4. 80.00
Answer and working

A. 32.77

p̂ = x̄/n = 4/5 = 0.8; expected trays = 100 × 0.8⁵ = 32.77. 0.8⁴ uses the wrong power; 100 × 0.2⁵ = 0.03 is the expected number with none germinating.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

7 · Bivariate normal: marginal and conditional distributions · medium

(X, Y) is bivariate normal with σ_X = 2, σ_Y = 3 and ρ = 0.5. What is the distribution of X − Y?

  1. Normal with mean μ_X − μ_Y and variance 19
  2. Normal with mean μ_X − μ_Y and variance 13
  3. Normal with mean μ_X − μ_Y and variance 5
  4. Normal with mean μ_X − μ_Y and variance 7
Answer and working

D. Normal with mean μ_X − μ_Y and variance 7

Linear combinations of a bivariate normal are normal. Var(X − Y) = 4 + 9 − 2(0.5)(2)(3) = 7. 13 ignores the covariance; 19 adds it with the wrong sign.

Further reading: Rohatgi and Saleh, An Introduction to Probability and Statistics; Johnson, Kotz and Balakrishnan, Continuous Univariate Distributions; Johnson, Kemp and Kotz, Univariate Discrete Distributions

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Probability Distributions & Sampling DistributionsThe full study manual, free ICAR AIEEA-PGFormat, sections and how it has changed

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