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ThesisItem Open Access On Construction and Analysis of Bio-assay Designs(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1984) Rai, Lajpat; Puri, P. D.ThesisItem Open Access Some Contributons to Jacknife Methodology and Its Applications(Department of Mathematics And Statistics College of Basic Sciences and Humanities Punjab Agricultural University, 1984) Saxena, Kuldeep Kuamr; Srivastava, O. P.ThesisItem Open Access Suitable Size and Shape of Plot and Block for Cotton crop(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1984) Panwar, Randhir Singh; Arya, A. DThesisItem Open Access Studies on the efficiency of des igns for wheat in relation to shape and size of plot and block(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1984) Sethi, Rajender; Kaushik, L. SThesisItem Open Access Estimation of Demand for Credit on Mechnized Farms of Kurukshetra District (Haryana_(College of Agriculture Chaudhary Charan Singh Haryana Agricultural University Hisar, 1984) Tyagi, Ashok Kumar; Pandey, Uma KantThesisItem Open Access Some Contributions to Jackknife Methodology and its Application(Chaudhary Charan Singh Haryana Agricultural Univesity, Hisar, 1984) Saxena, Kuldeep Kumar; Srivastava, O. P.besides•• sufficiency. efficiency end consistency. the unbid•Mend•• la also considered to be a desirable property of an estimator.. Let Q be any parameter of interest and A 9 be .,V reasonable estimator of 9. whence by evaluating the expectation of unbiased statistic may be derived provided the !(9) ls ., explicit function of Q. but often the complexity of the expected value presents a major drawback.,d then it ruy not be possible• to find an unbiased . statistic at all and •~ other .. method may be needed to /\improve 9 in the sense that its bi•• la reduced. such situations occur ln almost st. all types of • estimation problems.For last half century efforts have been made in problam the existing estimators or deriving new estimators with the help of various techniques. Jackknife is one such technique which •may be applied to various problems. In sec~ton l.l of this chapter, present the review the jackknife technique, used in bias reduction and obtaining confidence intervals . Section 1.2 and section 1.3 are d.voted to the review of two •-.Pl• jackknife technique ~ review of the application• of jackknife technique in linear regression models, respectively. Section 1.• l• d.woted to the review of the syn'lftetric functiona. 1ThesisItem Open Access Some Contributions to Jackknife Methodology and Its Applications(Chaudhary Charan Singh Haryana Agricultural Univesity, Hisar, 1984) Saxena, Kuldeep Kuamr; Srivastava, O. P.Besides nice properties of estimators , sometimes unbiasedness is also considered to be a desirable property all though unbiased estimators having Variances are not preferred In such cases there is a need either to modify these estimators or find other biased estimators with lower variances . Even for biased estimators, it is always possible to improve them by better techniques to lower the bias but not at the cost of increased variance . A method for reducing the bias in parametric estimation was introduced by Quenlouille {1949,56). which was later known as jackknife technique . The jackknife procedure depends upon judiciously dividing the data into groups, obtaining estimates from combination of these groups and then averaging the estimates. The notations used and procedure are given in (l .1.6) and (Ll.7). Its uses are two fold - one for reducing the bias of an estimator and second for obtaining approximate confidence interval in problems where other statistical procedures are difficult to applyThesisItem Open Access A New Design For Cluster Sampling(Chaudhary Charan Singh Haryana Agricultural Univesity, Hisar, 1984) Manjul, Jagan Nath; Nath, N.The main researches in the field of sampling designs is to provides designs which enable estimation of population characteristics with maximum possible precision with available resources or the use of minimum resources for obtaining estimates with given margin of error The choice of a sampling design depends upon operational convenience / cost involved and the precision required. The precision can be measured by variance Historically simple random sampling is the first method used in sample surveys and other methods may of viewed as its modifications to control its inherent drawbacks. In simple random sampling, units are drawn one after another and all possible samples of a given size are equally likely.ThesisItem Unknown Design and Analysis in tow and Tree Ways Stratification(Chaudhary Charan Singh Haryana Agricultural Univesity, Hisar, 1984) Chaudhary, P. S.; Chaduhary, E. LIn sample surveys, stratification as a well-known device used mainly to increase the precision of an estimator. In practice, one has a number of .factors for stratification but due to sample size and other design considerations the resulting number of factors that can be accommodated are so limited that sampler's options are quite restricted. Under such circumstances, one restricts either to the choice to most effective factor for stratification and abandons the others or chooses the most effective strata from various combinations of two or more factors. In that case, the resulting strata will be more heterogeneous than one would like, thus forgoing the ultimate aim of stratification. To overcome these restrictions, multiple stratification designs have been used ~y different workers under different labels like deep stratification (Tepping at al, 1943), two way stratification (Hartley, 1954), Bryant et al (1960), controlled selections (Goodman and Kish, 1950), probability lattice sampling (Jessen, 1973) whereby two or more Factors have been simultaneously used for stratification and multi way table of strata cells thus formed are used for sample selection and analysis.