Agricultural Statistics: A Guide for Competitive Examinations

by K.S.Kushwaha & Rajesh Kumar
ISBN: 9789381450314 | Binding: Paperback | Pages: 414 | Language: English | Year of Publishing: 2012
Length: 152 mm | Breadth: 29.2 mm | Height: 229 mm | Imprint: NIPA
USD 45.99 USD 42.00
Free Worldwide Delivery Within 10-15 Days By Indian Post (Traceable Methods)
Available through platform

The book entitled "Agricultural Statistics" has been designed for all U.G. and P.G. Students of "Pure Statistics, Agricultural Statistics, Biological & Social Sciences" and those who have to appear in competitive examinations of I.S.S., S.S.S., State's P.S.C.' and I.A.S. This book is also useful for faculties of "Department of Statistics" of Indian Universities.

The book is the outcome of 28 years of teaching experience of U.G., P.G. and Ph. D. students of different disciplines of Agriculture, Agil. Engg. and Agril. Statistics. in J.N.K.V.V. Jabalpur. 

K.S. Kushwaha: M.Sc., P.S.C.C., Ph.D. (Statistics), Recipient of Dr. Radhakrishanan Award (1992), Associate Professor (Statistics), Department of Mathematics & Statistics, Jawaharlal Nehru Krishi Vishwavidayalaya, Jabalpur, Madhya Pradesh, India,

Rajesh Kumar: M.Sc., P.S.C.C., Ph.D., (Statistics), Principal Scientist (Statistics), Indian Institute of Sugarcane Research (ICAR), Lucknow, Uttar Pradesh. India

Agricultural Statistics: A Guide for Competitive Examinations: 1: Introduction to Statistics, 2: Diagrammatic and Graphic Representation of Data, 3: Measures of Central Tendency, 4: Measures of Dispersion, 5: Theory of Probability, 6: Random Variables and Distribution, 7: Mathematical Expectation, 8: Generating Functions, Law of Large Numbers and Central Limit Theorems, 9: Discrete Distributions, 10: Continuous Distributions, 11: Theory of Testing of Hypotheses (Preliminaries), 12: Normal Distribution and Tests Based on It, 13: Chi-Square Distribution and Its Applications, 14: Exact Sampling Distributions and Related Small Sample Tests (F,t), 15: Simple and Multiple Correlation and Regression Analysis, Bibliography