AGRICULTURAL STATISTICS
Course Structure - at a Glance
1. Syllabus of Service Courses for M. Sc. and Ph. D. programmes of other disciplines
under Faculty of Agriculture and Faculty of Horticulture both
CODE COURSE TITLE CREDITS
STAT 500 ELEMENTARY STATISTICAL METHODS 3+1
STAT 501 STATISTICAL METHODS FOR RESEARCH WORKERS 2+1
STAT 502 STATISTICAL METHODS FOR BIOLOGY 2+1
STAT 503 EXPERIMENTAL DESIGN FOR RESEARCH WORKERS 2+1
STAT 504 STATISTICAL METHODS FOR SOCIAL SCIENCES 2+1
STAT 505 TIME SERIES ANALYSIS 2+1
STAT 506 LINEAR PROGRAMMING 2+1
STAT 507 ECONOMETRICS 2+1
STAT 508 BIOMETRICAL GENETICS 2+1
2. M. Sc. (Agricultural Statistics)
STAT 551 MATHEMATICAL METHODS-I 3+0
STAT 552 MATHEMATICAL METHODS-II 2+0
STAT 560 PROBABILITY THEORY 2+0
STAT 561 STATISTICAL METHODS 2+1
STAT 562 STATISTICAL INFERENCE 2+1
STAT 563 MULTIVARIATE ANALYSIS 2+1
STAT 564 DESIGN OF EXPERIMENTS 2+1
STAT 565 SAMPLING TECHNIQUES 2+1
STAT 566 STATISTICAL GENETICS 2+1
STAT 567 REGRESSION ANALYSIS 1+1
STAT 568 STATISTICAL COMPUTING 1+1
STAT 569 TIME SERIES ANALYSIS 1+1
STAT 570 ACTUARIAL STATISTICS 2+0
STAT 571 BIOINFORMATICS 2+0
STAT 572 ECONOMETRICS 2+0
STAT 573 STATISTICAL QUALITY CONTROL 2+0
STAT 574 OPTIMIZATION TECHNIQUES 1+1
STAT 575 DEMOGRAPHY 2+0
STAT 576 STATISTICAL METHODS FOR LIFE SCIENCES 2+0
STAT 577 STATISTICAL ECOLOGY 2+0
STAT 591 MASTER'S SEMINAR 1+0
STAT 599 MASTER'S RESEARCH 10+0
Note:
1. STAT 551 and STAT 552 are supporting courses. These are compulsory for all the students of Agricultural
Statistics.
2. STAT 560 - STAT 569 are core courses to be taken by all the students of Agricultural Statistics.
3. STAT 591 and STAT 599 are compulsory for all the students of Agricultural Statistics.
4. A student has to take a minimum of 36 credits course work, excluding the supporting courses,
seminar and research.
,3. Ph. D. (Agricultural Statistics)
STAT 601 ADVANCED STATISTICAL COMPUTING 2+1
STAT 602 SIMULATION TECHNIQUES 1+1
STAT 611 ADVANCED STATISTICAL METHODS 2+0
STAT 612 ADVANCED STATISTICAL INFERENCE 3+0
STAT 613 ADVANCED DESIGN OF EXPERIMENTS 2+0
STAT 614 ADVANCED SAMPLING TECHNIQUES 2+0
STAT 615 ADVANCED STATISTICAL GENETICS 2+0
STAT 616 STATISTICAL MODELING 1+1
STAT 617 ADVANCED TIME SERIES ANALYSIS 2+0
STAT 618 STOCHASTIC PROCESSES 2+0
STAT 619 SURVIVAL ANALYSIS 2+0
STAT 620 ADVANCED BIOINFORMATICS 2+0
STAT 621 ADVANCED ECONOMETRICS 2+0
STAT 651 RECENT ADVANCES IN THE FIELD OF 1+0
SPECIALIZATION
STAT 691 DOCTORAL SEMINAR I 1+0
STAT 692 DOCTORAL SEMINAR II 1+0
STAT 699 DOCTORAL RESEARCH 45+0
Note:
1. STAT 601 and STAT 602 are supporting courses. These are compulsory for all the students
of Agricultural Statistics.
2. STAT 691, STAT 692, STAT 651 and STAT 699 are compulsory for all the students of
Agricultural Statistics.
3. A student has to take a minimum of 18 credits course work, excluding the supporting courses,
seminar and research.
4. A student has to take two seminars.
PG Syllabuses, Department of Agricultural Statistics, UBKV [2]
,STAT 500 : Elementary Statistical Methods 3+1
(For those students who do not have sufficient statistical background)
Probability : Elementary concepts of probability; Addition theorem;
Conditional Probability; Multiplication theory; Independence
of events.
Statistical Methods : Population and its parameters; Sample and its statistics;
Frequency distribution; Graphical representation; Measures of
central tendency; Measures of dispersion; Moments; Simple
correlation and regression.
Probability Distributions : Binomial; Poisson & Normal
Sample Survey : Elementary concept; Advantages of sample survey over
census; Simple random sampling (SRS); SRSWR and
SRSWOR; Drawing of random sample & estimation of
average, total etc.; Sampling and non-sampling errors;
Concept of stratified random sampling.
Design of Experiments : One way and two way classification (orthogonal); Principles
of design; Uniformity trial and fertility contour map; Lay-out
and analysis of CRD, RBD and LSD.
Tests of Significance : Hypotheses; Two types of errors; Exact small sample tests: z,
t, χ 2 and F-tests.
Practicals : Based on above topics.
STAT 501 : Statistical Methods for Research Workers 2+1
Probability and : Preliminaries; Bayes' theorem; Repeated trials; Random
Distribution variable- Mathematical expectation and its laws; variance,
covariance etc.; Distribution: Binomial, Poisson, Normal.
Statistical Methods : Rank correlation; Correlation ratio; Intra-class correlation;
Multiple Regression involving three variables; Multiple and
partial correlation co-efficients; Stepwise multiple regression
analysis; Concept of auto-correlation function (ACF).
Tests of Significance : t, F, χ 2 -tests and large sample tests; Confidence intervals;
Transformation of Variables: Z-transformation.
Sample Survey : Stratified random sampling; Systematic sampling and cluster
sampling.
Design of Experiments : LSD; Uses of repeated Latin squares; Missing plot techniques
in RBD and LSD; Split-plot design; Multiple comparison
tests.
Practicals : Based on above topics.
PG Syllabuses, Department of Agricultural Statistics, UBKV [3]
, STAT 502: Statistical Methods for Biology 2+1
Probability and : Random variable and its expectation, variance etc., Binomial
Distribution Poisson, Normal, Negative Binomial and Log normal
distributions.
Statistical Methods : Multiple and partial correlation; Multiple regression;
Reproduction and mortality rates and their estimation;
Techniques for estimation of population number and growth.
Tests of Significance : Z, t, F and χ 2 -tests.
Design of Experiments : CRD, RBD and LSD and Split-plot design; Multiple
comparison tests; Missing plot techniques in RBD and LSD;
Elementary bio-assay and probit analysis.
Practicals : Based on above topics.
STAT 503: Experimental Design for Research Workers 2+1
Uniformity trails : Size and shape of pots and blocks; Lay-out and analysis of
CRD and RBD; Use of Repeated LSD's; Efficiency of
blocking; Missing plot techniques and analysis of covariance
in RBD and LSD Multiple comparison tests.
Factorial Experiments : Interpretation of main effects and interaction; Orthogonality
and partitioning of degrees of freedom; Analysis of 22, 23, 32
experiments; Concept of confounding and analysis of some
confounded factorial experiments; Split plot and strip plot
designs; Transformations; Analysis of groups of experiments.
Practicals : Based on above topics.
STAT 504: Statistical Methods for Social Sciences 2+1
Introduction : Frequency distribution; Principles governing their formation
and standard distributions.
Concept of Sampling : SRS and stratified random sampling; Sampling and non-
sampling errors and their remedial measures.
Tests of Significance : t, F, χ 2 -tests and large sample tests; Confidence intervals;
Transformation of Variables; Z-transformation; Distribution-
free statistics- run test, sign test; Wilcoxon sign-rank test,
Mann-Whitney U-test; Wald – Wolfowitz run test; Median
test etc.
Statistical Methods : Simple and multiple regression and prediction equations.
Application of : Factor analysis, Cluster analysis; Discriminant function and
Multivariate Analysis D2 statistics; Principal component analysis.
Praticals : Based on above topics.
PG Syllabuses, Department of Agricultural Statistics, UBKV [4]
Course Structure - at a Glance
1. Syllabus of Service Courses for M. Sc. and Ph. D. programmes of other disciplines
under Faculty of Agriculture and Faculty of Horticulture both
CODE COURSE TITLE CREDITS
STAT 500 ELEMENTARY STATISTICAL METHODS 3+1
STAT 501 STATISTICAL METHODS FOR RESEARCH WORKERS 2+1
STAT 502 STATISTICAL METHODS FOR BIOLOGY 2+1
STAT 503 EXPERIMENTAL DESIGN FOR RESEARCH WORKERS 2+1
STAT 504 STATISTICAL METHODS FOR SOCIAL SCIENCES 2+1
STAT 505 TIME SERIES ANALYSIS 2+1
STAT 506 LINEAR PROGRAMMING 2+1
STAT 507 ECONOMETRICS 2+1
STAT 508 BIOMETRICAL GENETICS 2+1
2. M. Sc. (Agricultural Statistics)
STAT 551 MATHEMATICAL METHODS-I 3+0
STAT 552 MATHEMATICAL METHODS-II 2+0
STAT 560 PROBABILITY THEORY 2+0
STAT 561 STATISTICAL METHODS 2+1
STAT 562 STATISTICAL INFERENCE 2+1
STAT 563 MULTIVARIATE ANALYSIS 2+1
STAT 564 DESIGN OF EXPERIMENTS 2+1
STAT 565 SAMPLING TECHNIQUES 2+1
STAT 566 STATISTICAL GENETICS 2+1
STAT 567 REGRESSION ANALYSIS 1+1
STAT 568 STATISTICAL COMPUTING 1+1
STAT 569 TIME SERIES ANALYSIS 1+1
STAT 570 ACTUARIAL STATISTICS 2+0
STAT 571 BIOINFORMATICS 2+0
STAT 572 ECONOMETRICS 2+0
STAT 573 STATISTICAL QUALITY CONTROL 2+0
STAT 574 OPTIMIZATION TECHNIQUES 1+1
STAT 575 DEMOGRAPHY 2+0
STAT 576 STATISTICAL METHODS FOR LIFE SCIENCES 2+0
STAT 577 STATISTICAL ECOLOGY 2+0
STAT 591 MASTER'S SEMINAR 1+0
STAT 599 MASTER'S RESEARCH 10+0
Note:
1. STAT 551 and STAT 552 are supporting courses. These are compulsory for all the students of Agricultural
Statistics.
2. STAT 560 - STAT 569 are core courses to be taken by all the students of Agricultural Statistics.
3. STAT 591 and STAT 599 are compulsory for all the students of Agricultural Statistics.
4. A student has to take a minimum of 36 credits course work, excluding the supporting courses,
seminar and research.
,3. Ph. D. (Agricultural Statistics)
STAT 601 ADVANCED STATISTICAL COMPUTING 2+1
STAT 602 SIMULATION TECHNIQUES 1+1
STAT 611 ADVANCED STATISTICAL METHODS 2+0
STAT 612 ADVANCED STATISTICAL INFERENCE 3+0
STAT 613 ADVANCED DESIGN OF EXPERIMENTS 2+0
STAT 614 ADVANCED SAMPLING TECHNIQUES 2+0
STAT 615 ADVANCED STATISTICAL GENETICS 2+0
STAT 616 STATISTICAL MODELING 1+1
STAT 617 ADVANCED TIME SERIES ANALYSIS 2+0
STAT 618 STOCHASTIC PROCESSES 2+0
STAT 619 SURVIVAL ANALYSIS 2+0
STAT 620 ADVANCED BIOINFORMATICS 2+0
STAT 621 ADVANCED ECONOMETRICS 2+0
STAT 651 RECENT ADVANCES IN THE FIELD OF 1+0
SPECIALIZATION
STAT 691 DOCTORAL SEMINAR I 1+0
STAT 692 DOCTORAL SEMINAR II 1+0
STAT 699 DOCTORAL RESEARCH 45+0
Note:
1. STAT 601 and STAT 602 are supporting courses. These are compulsory for all the students
of Agricultural Statistics.
2. STAT 691, STAT 692, STAT 651 and STAT 699 are compulsory for all the students of
Agricultural Statistics.
3. A student has to take a minimum of 18 credits course work, excluding the supporting courses,
seminar and research.
4. A student has to take two seminars.
PG Syllabuses, Department of Agricultural Statistics, UBKV [2]
,STAT 500 : Elementary Statistical Methods 3+1
(For those students who do not have sufficient statistical background)
Probability : Elementary concepts of probability; Addition theorem;
Conditional Probability; Multiplication theory; Independence
of events.
Statistical Methods : Population and its parameters; Sample and its statistics;
Frequency distribution; Graphical representation; Measures of
central tendency; Measures of dispersion; Moments; Simple
correlation and regression.
Probability Distributions : Binomial; Poisson & Normal
Sample Survey : Elementary concept; Advantages of sample survey over
census; Simple random sampling (SRS); SRSWR and
SRSWOR; Drawing of random sample & estimation of
average, total etc.; Sampling and non-sampling errors;
Concept of stratified random sampling.
Design of Experiments : One way and two way classification (orthogonal); Principles
of design; Uniformity trial and fertility contour map; Lay-out
and analysis of CRD, RBD and LSD.
Tests of Significance : Hypotheses; Two types of errors; Exact small sample tests: z,
t, χ 2 and F-tests.
Practicals : Based on above topics.
STAT 501 : Statistical Methods for Research Workers 2+1
Probability and : Preliminaries; Bayes' theorem; Repeated trials; Random
Distribution variable- Mathematical expectation and its laws; variance,
covariance etc.; Distribution: Binomial, Poisson, Normal.
Statistical Methods : Rank correlation; Correlation ratio; Intra-class correlation;
Multiple Regression involving three variables; Multiple and
partial correlation co-efficients; Stepwise multiple regression
analysis; Concept of auto-correlation function (ACF).
Tests of Significance : t, F, χ 2 -tests and large sample tests; Confidence intervals;
Transformation of Variables: Z-transformation.
Sample Survey : Stratified random sampling; Systematic sampling and cluster
sampling.
Design of Experiments : LSD; Uses of repeated Latin squares; Missing plot techniques
in RBD and LSD; Split-plot design; Multiple comparison
tests.
Practicals : Based on above topics.
PG Syllabuses, Department of Agricultural Statistics, UBKV [3]
, STAT 502: Statistical Methods for Biology 2+1
Probability and : Random variable and its expectation, variance etc., Binomial
Distribution Poisson, Normal, Negative Binomial and Log normal
distributions.
Statistical Methods : Multiple and partial correlation; Multiple regression;
Reproduction and mortality rates and their estimation;
Techniques for estimation of population number and growth.
Tests of Significance : Z, t, F and χ 2 -tests.
Design of Experiments : CRD, RBD and LSD and Split-plot design; Multiple
comparison tests; Missing plot techniques in RBD and LSD;
Elementary bio-assay and probit analysis.
Practicals : Based on above topics.
STAT 503: Experimental Design for Research Workers 2+1
Uniformity trails : Size and shape of pots and blocks; Lay-out and analysis of
CRD and RBD; Use of Repeated LSD's; Efficiency of
blocking; Missing plot techniques and analysis of covariance
in RBD and LSD Multiple comparison tests.
Factorial Experiments : Interpretation of main effects and interaction; Orthogonality
and partitioning of degrees of freedom; Analysis of 22, 23, 32
experiments; Concept of confounding and analysis of some
confounded factorial experiments; Split plot and strip plot
designs; Transformations; Analysis of groups of experiments.
Practicals : Based on above topics.
STAT 504: Statistical Methods for Social Sciences 2+1
Introduction : Frequency distribution; Principles governing their formation
and standard distributions.
Concept of Sampling : SRS and stratified random sampling; Sampling and non-
sampling errors and their remedial measures.
Tests of Significance : t, F, χ 2 -tests and large sample tests; Confidence intervals;
Transformation of Variables; Z-transformation; Distribution-
free statistics- run test, sign test; Wilcoxon sign-rank test,
Mann-Whitney U-test; Wald – Wolfowitz run test; Median
test etc.
Statistical Methods : Simple and multiple regression and prediction equations.
Application of : Factor analysis, Cluster analysis; Discriminant function and
Multivariate Analysis D2 statistics; Principal component analysis.
Praticals : Based on above topics.
PG Syllabuses, Department of Agricultural Statistics, UBKV [4]
