PHD in Agricultural Statistics in IARI Eligibility, Syllabus and Admission

PHD in Agricultural Statistics in IARI Eligibility, Syllabus and Admission.

Online Notification is Published on- March

Sub-discipline-Agricultural Statistics 

Number of Seats – Agricultural Statistics General 6 and SC-1, ST-1, and OBC-1

Age Limit – The minimum age for admission shall be 21 years. No relaxation is admissible regarding
the minimum age limit.

Qualification for Admission to Agricultural Statistics-  M.Sc./M.Sc.(Ag)/M.Tech./M.E. in Agricultural Statistics/Statistics/Mathematical Statistics/ Bio-Statistics/ Professional Statisticians’ Certificate Course (PSCC) of IASRI

Syllabus  PART-II AND III Agricultural Statistics

Elements of probability theory, concepts of random variable and distribution function, conditional probability; Bayes’ theorem; moments; moment generating and characteristic functions; Chebychev’s inequality, law of large numbers; limit theorems; univariate (discrete and continuous) distributions; sampling distributions, transformations; multivariate normal distribution, Wishart’s distribution, Hotelling’s T2; discriminant function; elements of stochastic processes; theory of point estimation; Cramer-Rao inequality; Rao-Blackwell theorem; methods of estimation; confidence intervals; testing of hypothesis, tests of simple hypothesis against simple or composite hypothesis; likelihood ratio test; sequential probability ratio test; large sample tests; non-parametric tests.

  • Concepts of sampling and non-sampling errors; simple random sampling; stratified sampling, allocation of sample to strata gain due to stratification; ratio and regression methods of estimation; cluster sampling; two stage sampling; systematic sampling; sampling with probability proportional to size with replacement.
  • Principles of design of experiments; uniformity trials; completely randomized, randomized block and latin square designs; missing values in randomized block and latin square designs; analysis of non-orthogonal data in two-way classification (without interaction); factorial experiments and confounding in symmetrical factorial experiments – design and anaysis of 2n and 3n experiments; split and strip plot designs; balanced incomplete block design (BIBD)- parametric relations and general properties; analysis of BIBD with recovery of interblock information.
  • Statistical analysis for segregation and linkage; random mating and equilibrium in large populations; inbreeding – effects of finite population size; polygenic systems for quantitative characters; genetic variance and correlation; heritability, repeatability; individual, family and combined selections; selection for improving several characters; cross-breeding.

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