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OBJECTIVE AGRICULTURE STATISTICS (2nd Fully Revised And Enlarged Edition)

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Individual Price: ₹ 350.00 ₹ 315.00 + Tax

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This book entitled "Objective Agriculture Statistics - 2nd Revised Edition is an enlarged version of the previously published book in year 2011. This book comes with additional topics on "Sample Survey" which is included in the book as "Supplementary Part".

New to This Edition, 94 pages covering

(1)   Sampling on Successive Occasions

(2)   Non- Sampling Errors

(3)   National Sample Surveys

(4)   Agricultural Statistics system in India.

(5)   10 Model Papers

It will provide better coverage to the students and will help them appear in various competitive examinations as cited in first edition. 

0 Start Pages

The book entitled “Objective Agriculture Statistics” has been designed for all 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., I.A.S., State’s P.S.C.’s. This book is useful for faculties of “Department of statistics” of Indian Universities. The book is the outcome of 26 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. The content of the book covers the syllabus on the topics “The Theory of Sample Survey Design, Designs of Experiment, ANOVA, ANCOVA Techniques, Transformation of Original Data and Non Parametric Methods.”

1 Sample Survey Theory

In this chapter some preliminary terminologies have been provided which are very much useful and frequently used in dealing with the theory of sample surveys and its application.

1 - 12 (12 Pages)
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2 Sample Random Sampling (S.R.S.W.O.R. & S.R.S.W.R.)

Q.1 SRSWOR scheme is better (more efficient) them SRSWR scheme. Q.2 The sampling variance of sample mean under SRSWOR scheme is more than that in SRSWR scheme. .3 The sample variance s2 is an unbiased estimate of population M.S. (S2 ) in case of SRSWOR scheme.

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3 Stratified Random Sampling

Q.1 If the sampling units of the population are of heterogeneous nature then stratified random sampling scheme is suitable for sample survey to be conducted. Q.2 In stratatified random sampling scheme, the strata are homogeneous within themselves but heterogeneous between themselves.

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4 Cluster Sampling

Q.1 In the theory of cluster sampling, if the population is divisible into smallest, distinct and identifiable units then this smallest unit is known as elementary unit (element) of the population. Q.2 A group of elementary units in context of sample survey theory is known as cluster.

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5 Systematic Sampling

Q.1 Systematic random sampling or systematic sampling, both are different sampling schemes. Q.2 The pattern usually followed in selecting a systematic sample is a simple pattern involving a constant spacing of units in the sample.

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6 Ratio Product and Regression Methods of Estimation

Q.1 Informations available on an auxiliary variable X which is highly correlated with the study variable y, can be utilized in improving the sampling design for the study variable y. Q.2 Information on auxiliary variable X can be used for stratification of population for the study character y.

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7 Multistage Sampling

Q.1 Cluster sampling restricts the spread of sample over the population which results generally in increased sampling variance of estimators under considerataion. Q.2 In adopting cluster sampling, few selected clusters are enumerated partially.

95 - 106 (12 Pages)
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8 Varying Probability Samplings

Q.1 A sampling procedure in which the units are selected with probability proportional to their some size measure, is known as sampling procedure with probability proportional to size (P.P.S.) Notations: Let there be a population of N units say Yi , (i = 1,2, ......... N), YN with their selection probabilities Pi (i=1, 2........... , N). Here Pi ? Pj V i ? J. = 1, 2, .............. N. Let yi , (i = 1, 2, ...................n) be the sample drawn from the population with probability of selection pi (i = 1, 2 -, n).

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9 Preliminaries and Basic Principles of Design of Experiments

Q.1 An experiment is a means of getting an answer to the question which arises in the mind of an experimenter (reseacher). Q.2 An experiment may be planned for not to compare the yield of several varieties of wheat.

119 - 138 (20 Pages)
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10 ANOVA (One Way) Classification

Q.1 According to prof. R. A. Fisher “ANOVA” is not the separation of variance assignable to one group of causes from the variance assignable to another group of causes. Q.2 The basic purpose of ANOVA technique is to test the homogeneity (equality) of several means.

139 - 152 (14 Pages)
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11 C.R.D., R.C.B.D. Latin Square Design

Q.1 We can apply the change of origin or change of scale or change of origin and scale both to the original data in case of applying ANOVA technique to make the analysis easy and speedy. Q.2 The conclusions drawn from ANOVA based on transformed data or original data are different.

153 - 176 (24 Pages)
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12 Factorial Experiment

Q.1 Factorial experiment is not a design. Q.2 In factorial experiment, all possible combinations of two or more than two factors are not considered

177 - 202 (26 Pages)
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13 Split Plot Design

Q.1 If two type ot factors, say (A & B) have to be studied in the same experiment where A requires larger plot size and B requires smaller plot size and structure of the experiment is that of plots within blocks and blocks within replication then such layout is known as split plot design.

203 - 214 (12 Pages)
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14 Strip Plot Design

Q.1 Let there be two factors A and B with p and q levels respectively which are applied to the larger strip by dividing the experimental material into p rows and q columns. The factors A and B are applied at random to these rows and columns respectively. Such a layout is known as strip plot design.

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15 Progeny Row Trial and Compact Family Block Design

Q.1 The replicated experiment designed to compare a number of parent plants w. r. to some attribute under study is known as “Progeny row trial?

227 - 234 (8 Pages)
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16 Analysis of Covariance (ANCOVA)

Q.1 Analysis of covariance is an extension of ANOVA. Q.2 In an ANCOVA technique, observations are taken on more than one variable from each experimental unit.

235 - 254 (20 Pages)
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17 Some Miscellaneous Questions on ANOVA Technique

Q.1 In random effect model, the treatments are taken as a random sample of treatments drawn from a large group of T treatments. Q.2 In varietal trials for plant breeding or genetics, the appropriate statistical model is not the random effect model.

255 - 270 (16 Pages)
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18 Transformation of Data to Apply ANOVA Technique

Q.1 In addition to the assumption of ANOVA, the other point which is given due consideration by the statistician is “The stability of variance.” Q.2 In any investigation, if it is possible to incorporate the “randomisation procedure” then it is customary to rely on “ Randomisation” to break up any “correlation among experimental errors”

271 - 280 (10 Pages)
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19 Non Parametric Methods

Q.1 The most fundamental assumption to be followed by random variable for using the standard method (parametric statistic) or parametric inference is that the random variable follows normal distribution. Q.2 The standard parametric techniques are not useful for estimating parameters and testing hypothesis about them.

281 - 290 (10 Pages)
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20 Additional Topics on Sample Surveys

Q.1 In applying varying probability sampling for information of population total of X, it is required to know the values of selection probabilities Pi (i = 1, 2, 3,..., N). Q.2 The technique of “Double Sampling” was first time formulated by Jayman, (1938) in connection of collecting information on strata sizes in stratified random sampling scheme.

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21 Bibliography

Cochan W.G. (1946). Relative Accuracy of Systematic and Stratified Random Sampling for a Certain Class of Populations. Ann. Math. Statist, 17, 164- 177. Cochan, W.G. (1977). Sampling Technique, 3rd edition, Wiley Eastern Ltd., New Delhi.

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22 Model Papers

1. Which of the following states has nutrient use of < 100 kg/ ha? (a) Madhya Pradesh                (b) Karnataka (c) West Bengal                       (d) Uttar Pradesh 2. Which of the following is the leading state in maize production (a) Bihar                                   (b) Uttar Pradesh (c) Punjab                                (d) Gujarat

339 - 402 (64 Pages)
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