Combined NET/ARS/SMS/STO recruitment: preliminary (objective), mains (descriptive, discipline paper) and interview for ARS.
Sections
Preliminary: objective discipline paper
Mains: descriptive Agricultural Statistics paper
Interview / personality test
Over the years
Built from Laisha's knowledge because the official page could not be opened or was not found during research (web search quota exhausted); confirm against the body's current notification before relying on it. ARS scientists in Agricultural Statistics are posted mainly to ICAR-IASRI and to statistics units of other ICAR institutes. Mark split and current scheme not verified.
Most poor people live in rural areas and earn their living from farming
Farm incomes are not taxed, so growth reaches households in full
Answer and working
C. Most poor people live in rural areas and earn their living from farming
Where most of the poor work in agriculture, growth in the sector raises the incomes of the poor directly; this pattern is well documented in development economics.
Agriculture for Statisticians · Importance of agriculture, forestry, livestock and fisheries in national economies
2. A double-precision IEEE 754 number has 52 fraction bits. Its precision is about:
7 significant decimal digits
52 significant decimal digits
15–17 significant decimal digits
32 significant decimal digits
Answer and working
C. 15–17 significant decimal digits
2⁻⁵² ≈ 2.2 × 10⁻¹⁶; single precision gives about 7 digits.
Computer Science Fundamentals: Architecture, Data Structures, Networks & Operating Systems · Number systems, Boolean algebra and logic circuits
3. Two quality checks on a seed lot are passed with probabilities 0.8 and 0.7. Nothing is known about how the checks are related. What is the smallest possible probability that a lot passes both?
0
0.5
0.7
0.56
Answer and working
B. 0.5
Bonferroni's inequality gives P(A ∩ B) ≥ P(A) + P(B) − 1 = 0.8 + 0.7 − 1 = 0.5, and this bound is attained when the failures never overlap. 0.56 is the value only under independence; 0.7 is the largest possible value; 0 is impossible because the two failure probabilities add to only 0.5.
Probability Theory · Sample spaces, sigma-fields and the axioms of probability
4. Counts of aphids on 200 leaves have mean 1.5 and variance 4.2. Which conclusion and moment estimate are correct?
The counts are aggregated; negative binomial k ≈ 0.83
The counts are aggregated; negative binomial k ≈ 2.80
The counts are regular; binomial with p ≈ 0.64 fits
The counts are random; Poisson with λ ≈ 1.50 fits
Answer and working
A. The counts are aggregated; negative binomial k ≈ 0.83
Index of dispersion 4.2/1.5 = 2.8 > 1 means clumping. Moment estimate k̂ = x̄²/(s² − x̄) = 2.25/2.7 = 0.83. 2.80 is the dispersion index itself, not k. A binomial would need variance below the mean.
Probability Distributions & Sampling Distributions · Discrete distributions: Bernoulli, binomial, Poisson, geometric, negative binomial, hypergeometric and multinomial
5. In 100 days of records, 40 transitions start from wet days, and 26 of them lead to another wet day. What is the maximum-likelihood estimate of P(wet → wet)?
0.40
0.65
0.35
0.26
Answer and working
B. 0.65
p̂₁₁ = n₁₁/n₁. = 26/40 = 0.65. Dividing by all 100 days gives 0.26.
Stochastic Processes · Markov chains: transition matrices and Chapman-Kolmogorov equations
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