Admission Process for Ph.D (Statistics) in Calcutta University
Master degree holders in Statistics or allied subjects can seek admission to Ph.D (Statistics) in Calcutta University. Admission process is done on the basis of a written test and interview. There will be objective model as well as short answer type questions for the written test. Topics like Real Analysis, Probability, Bayesian Analysis, Poisson process, and Multivariate Analysis are asked. Those with NET / SET (Mathematical Sciences) qualification are exempted from the written test.
Eligibility Criteria for Ph.D (Statistics) in Calcutta University
M.Sc degree in Statistics or allied subjects from any of the recognized University is the basic educational qualification required.
Admission to Ph.D (Statistics) in Calcutta University
Admission process is done on the basis of a written test and interview. Those with NET / SET (Mathematical Sciences) qualification or UGC Teachers’ Fellowship are exempted from written test. Candidates having completed M.Phil degree in Statistics or those with a valid score in GATE (Mathematics) can also skip the written test. But all these candidates have to attend the interview session.
Exam Pattern for Ph.D (Statistics) Entrance Test in Calcutta University
There will be objective model as well as short answer type questions for the written test. Out of the total of 25 multiple choice questions, candidates are required to answer 20 only. In case, if candidate answers more than 20 questions, then the first 20 will be considered for evaluation. Marks given for each correct answer is 2.5. The number of short answer questions asked for the test is 15. Out of this, candidates need to answer only 10. Each correct answer carries 5 marks. In this case also, if candidate accidentally answers more than 10 questions, then the first 10 will be evaluated. Candidates who qualify the written test will be considered for interview.
Syllabus for Ph.D (Statistics) Entrance Test in Calcutta University
 Real Analysis
 Probability
 Sets
 Linear Algebra and Linear Programming
 Vectors and Matrices
 Sampling Distributions
 Large Sample Theory
 Markov chains
 Statistical Inference
 Linear Models
 Regression Analysis
 Scheffe’s theorem
 Design of Experiments
 Sample Surveys
 Bayesian Analysis
 Decision Theory
 Slutsky’s theorem
 Resampling Techniques
 Stochastic Processes
 Time Series Analysis
 Poisson process
 Multivariate Analysis
 Applied Multivariate Analysis
 Clustering
 Classification and discrimination procedures
 Principal Component Analysis
 Factor Analysis
 Canonical Correlations
Intake capacity for the course is 69. Thorough exam preparation is required to clear the written test. Text books prescribed for B.Sc (Statistics) in Calcutta University can be University can be used for study. Study materials can also be collected from web. Those who clear the selection procedures can join the course by November.

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