Course Introduction

This is post-graduate level course in the Department of Agronomy and compulsory for all MSc agronomy students. This course provided basic knowledge about how to conduct the field experiments with accurate layout plant. This course also provides the knowledge to collect the data in filed and analyze the data for presentation. This course will introduce the method of collecting data and analyze the data and  develop a skill to presentation in tabulated or graphical form. This course is very helpful for the students to write their thesis especially results and discussion.

Objective:To plan the experiments according to different design and layout therein the field and to collect the data, analysis it and interpretation.

Theory

Methods of scientific inquiry; general types of experiments; Principles of experimental design; Planning, layout and conducting field experiments; Recording research observations; Transformation of data ; Planned F test; Data processing, analyses and its statistical interpretation; Means separation; Probability; F and t distributions; Regression and correlation; Research results reporting.

Practical

Statistical calculations based on sample data; Exercise in the layout of experiments; Transformation of Experimental data; Preparation of analysis of variance table; Use of different tests of significance; Factorial experiments and their uses in scientific research; Reporting results of experiment; calculation of linear regression and correlations; Use of statistical packages for data.

Outcomes;

The main aim of the course is to train the students to design and make layout of the field crop experiments keeping in view different experimental designs to collect the data on a scientific basis. They may be able to analyze and interpret the collected data. On completion of course, the students will have the ability to plan experiments according to suitable design and layout these in the field. They may have scientific approach to collect, analyze and interpret the data.

Books Recommended

1. Das, N.R. 2006. Agronomic Research Management. Agrotech Publishing Academy, Udaipur, India.
2. Lawal, B. 2014. Applied Statistical Methods in Agriculture, Health and Life Sciences. Springer.
3.  Hastie, T., R. Tibshirani, R.J. Friedman and J. Franklin. 2005. The elements of statistical learning: data mining, inference and prediction. The Mathematical Intelligencer,
4. James, G., D. Witten, T. Hastie and R. Tibshirani. 2013. An introduction to statistical learning .New York: springer.
5. Gomez, K.A. and A.A. Gomez. 1984. Statistical procedures for agricultural research. John Wiley & Sons.

   Week	Topics and Readings	Book with Page No.
   1	Detailed Discussion about course and course contents.	(Approved UOS curriculum for M.Sc.)
   	The Preview of background knowledge about statistics.	--------------
   	The brief review and history of layout designs and execution	----------------
   2	Introduction, definition and importance	Book 6, Chapter I, Page 1-7
   	Statistics and scientific method	Book 6, Chapter I, Page 1-4
   	Methods of scientific inquiry	Book 3, Chapter II, Page 8-16
   3	Characteristics of a well planned experiment	Book 3, Chapter II, Page 31-38) 11
   	Steps in experimentation	Book 7, Chapter I, Page 7-10
   	Principles of experimental design	Book 3, Chapter VI, Page 88-98
   4	Types and classification of experiments	Book 4, Chapter I, Page 1-4
   	Sources of variation in field experiments	Book 4, Chapter I, Page 5
   	Planning and layout of the experiments	Book 4, Chapter I, Page 6-7
   5	Conducting field experiments	Book 4, Chapter I, Page 8-10
   	Observing and collecting data	Book 4, Chapter I, page 12
   	Analyzing and interpreting data	Book 4, Chapter I, Page 13
   6	Summarizing results and report writing	Book 4, Chapter I, Page 14
   	Publishing results and technology transfer	Book 4, Chapter I, Page 15-16
   	Discussion
   7	Probability – Normal distribution	Book 3, Chapter III, Page 31-40
   	t distribution and confidence limit	Book 7, Chapter II, Page 13-27
   	F distribution	Book 7, Chapter II, Page 13-27
   8	ANOVA and t test,	Book 7, Chapter II, Page 13-27
   	ANOVA with two samples	Book 7, Chapter II, Page 13-27
   	A population of mean differences, t test for significance	Book 7, Chapter II, Page 13-27
   9	Mid Term Exam
   10	Completely randomized design, layout and randomization	Book 3, Chapter VII, Page 99-128
   	Component in ANOVA, steps in ANOVA	Book 7, Chapter VI, Page 47-52
   	Mean separation	Book 3, Chapter VII, Page 99-128
   11	Randomized complete block design, layout, randomization and ANOVA	Book 3, Chapter VIII, Page 132-145
   	Mean separation, LSD and multiple range test	Book 7, Chapter V, Page 54-56
   	Planned F test, orthogonal contrast, class comparison, trend comparison	Book 7, Chapter VI, Page 61-75
   12	Layout, randomization and ANOVA	Book 6, Chapter XV, Page 235-260
   	Factorial experiments	Book 6, Chapter XII, Page 161-184
   	CRD and RCBD in factorial arrangement	Book 6, Chapter XII, Page 161-184
   13	Transformations of data	Book 7, Chapter XII, Page 139-164
   	Various types of transformation	Book 7, Chapter XII, Page 139-164
   	Various types of transformation	Book 7, Chapter XII, Page 139-164
   14	Independence of mean	Book 7, Chapter XII, Page 139-164
   	Independence of variances	Book 7, Chapter XII, Page 139-164
   	Discussion
   15	Regression and correlation	Book 6, Chapter VII, Page 71-84
   	Linear Correlation	(Book 7, Chapter XIII, Page 167-192)
   	The regression line and confidence limits	Book 7, Chapter XIII, Page 167-192
   16	Curvilinear relations	Book 7, Chapter XIV, Page 195-220
   	Shortcut and other regression methods	Book 7, Chapter XV, Page 229-243
   	Correlation and regression for more than two variables	Book 7, Chapter XVI, Page 247-264
   17	Multiple correlation and regression	Book 3, Chapter XVI, Page 277-301
   	Analysis of covariance	Book 3, Chapter XV, Page 305-325
   18	Improving precision	Book 7, Chapter XVII, Page 283-293

Time Table

Tuesday 2:00

Wednesd:ay 9:40

Thursday 2:00

Friday 8:50

KEY DATES

Mid test : April 27 to May 4, 2020

Final Examination: June 22-26, 2020

Result Declaration July 03, 2020