Research & reviews journal of statistics (vol3, issue2)

Page 1

Research & Reviews Journal of Statistics (RRJHS)

(RRJoST) ISSN : 2348-7909

Volume 1, Issue 1-3 Compilation 2012

May - August 2014

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R. Vijayaraghavan Department of Statistics, Bharathiar University, Coimbatore 641 046,Tamil Nadu, India.

Kedar Nath Singh Yadava Deptt. of Statistics, BHU, Varanasi-5, India.

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Prof. Harinder Singh Professor & Head Department of Mathematics, Jaypee University of Information Technology, Waknaghat , India.

Arijit Chaudhari Honorary Visiting Professor, Applied Statistics Unit, Indian Statistical Institute, India.

Rajyaguru Arti Department of Statistics Veer Narmad South Gujarat University, Udhna Magdalla Road.

Dr. Balkishan Sharma Associate Professor (Biostatistics), Department of Community Medicine, Sri Aurobindo Medical College and P. G. Institute, Indore (M. P.), India.


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STM JOURNALS

I take the privilege to present the hard copy compilation for the [Volume 3 Issue (2)] of Research & Reviews: Journal of Statistics. The intension of RRJoST is to create an atmosphere that stimulates creativeness, research and growth in the area of Journal of Statistics. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. RRJoST provides an outlet for Research findings and reviews in areas of Statistics found to be relevant for National and International recent developments & research initiative. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain of Statistics. Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for their continued support and invaluable contributions and suggestions in the form of authoring writeups/ reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviews findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra Director STM Journals


Research & Reviews : Journal of Statistics

Contents

1. Coefficient Estimation of Regression Model and Hypothesis Testing by Bootstrap Method Md. Siddikur Rahman

1

2. A Generalized Product Method of Estimation in Two Phase Sampling Balkishan Sharma, Housila P. Singh, Rajesh Tailor

8

3. Mann-Whitney Test for Imprecise Observations V. S. Vaidyanathan

16

4. Construction of Neighbour Balanced Nested Row Column Designs and Âľ-Resolvable All Order Neighbour Balance Design by using Mutually Orthogonal Latin Squares Aatish Kumar Sahu, Anurup Majumder

21


Research & Reviews: Journal of Statistics ISSN: 2278-2273 (online), ISSN: 2348-7909 (print) Volume 3, Issue 2 www.stmjournals.com

Coefficient Estimation of Regression Model and Hypothesis Testing by Bootstrap Method Md. Siddikur Rahman Department of Statistics, Begum Rokeya University, Rangpur, Bangladesh

Abstract The main concern of statistical inference is to achieve accurate result and to make proper decision on the basis of sample observations. But in some practical cases, it is not possible to reach the goal of statistics for the lack of desired number of sample. When the sample size is small and/or the empirical distribution is unknown, we have to use bootstrapping method to increases the accuracy of the results. The bootstrap method of regression analysis is discussed in this paper with practical example. In small sample case, there is a possibility of violating the normality assumption of the error. To avoid this problem, the bootstrap method gives us better result. A key objective in classical testing of statistical hypothesis is achieving good power of the test. To compare the existing simulation based test approach to bootstrap approach test, we calculated the power of the test and then graphically shown in this paper. We have conducted a hypothesis testing of regression coefficient. We observe that power of the test with bootstrap approach is much higher than the power of simulation approach. Actually, the power of the tests is compared and the better result of bootstrap method is found.

Keywords: Linear Regression model, Regression coefficient, Hypothesis testing, Bootstrapping

RRJoST (2014)Š STM Journals 2014. All Rights Reserved


Research & Reviews: Journal of Statistics ISSN: 2278-2273 (online), ISSN: 2348-7909 (print) Volume 3, Issue 2 www.stmjournals.com

A Generalized Product Method of Estimation in Two Phase Sampling Balkishan Sharma1*, Housila P. Singh2, Rajesh Tailor2 1

Department of Community Medicine, Sri Aurobindo Medical College & P. G. Institute, Indore, M. P., India 2 School of Studies in Statistics, Vikram University, Ujjain, M. P., India

Abstract This paper proposes a generalized product type estimator for population mean using two phase sampling in the presence of available knowledge on second auxiliary variable z, when the population mean of the main auxiliary variable x is not known. It is shown that the proposed estimator is more efficient than the usual unbiased estimator, the double sampling product estimator and Sahoo et al.’s estimator. An empirical study is carried out to assess the comparative performance of the proposed estimator over other estimators.

Keywords: Study Double sampling

variate,

Auxiliary

variate,

Bias,

Mean

RRJoST (2014)Š STM Journals 2014. All Rights Reserved

squared

error,


Research & Reviews: Journal of Statistics ISSN: 2278-2273 (online), ISSN: 2348-7909 (print) Volume 3, Issue 2 www.stmjournals.com

Mann-Whitney Test for Imprecise Observations V. S. Vaidyanathan* Department of Statistics, Pondicherry University, Puducherry, India Abstract Mann-Whitney test is a non-parametric test that is used to identify whether the probability distributions corresponding to two populations are identical. This article extends the Mann-Whitney test by treating the underlying observations as imprecise values. The test procedure is developed by using a novel approach to rank fuzzy values based on the concepts of “Credibility Theory” proposed by Liu (2007) for studying the behavior of fuzzy phenomena. Numerical illustration is provided through simulation by representing the observations as triangular fuzzy numbers.

Keywords: Credibility measure, Fuzzy number, Membership function, Ranking fuzzy values, Mann-Whitney test statistic

RRJoST (2014)© STM Journals 2014. All Rights Reserved


Research & Reviews: Journal of Statistics ISSN: 2278-2273 (online), ISSN: 2348-7909 (print) Volume 3, Issue 2 www.stmjournals.com

Construction of Neighbour Balanced Nested Row Column Designs and µ-Resolvable All Order Neighbour Balance Design by using Mutually Orthogonal Latin Squares Aatish Kumar Sahu1*, Anurup Majumder2 1

SASRD, Nagaland University, Medziphema, Nagaland-797106 Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, W. Bengal-741252

2

Abstract Latin Squares are known to possess very unique features and so is its utility. Construction of Balance Incomplete Block with nested Row Column (BIBRC) designs having Neighbor Balanced properties have been developed on the concept of Mutually Orthogonal Latin Squares (MOLS) of strength v, v being natural number and if it has at least four MOLS available. The designs used minimal blocks and found to be exact neighbor balanced with respect to rows, columns as well as diagonally. In the second part of this paper, concept of MOLS is used in construction of µ-Resolvable Balance Incomplete Block Designs following Subramani [1]. The designs fulfill the criteria of one-dimensional All Order Neighbor Balanced (AONB), developed with v number of treatments, v being natural number, if and only if, there is availability of minimum two Mutually Orthogonal Latin Squares for v. These designs showed all order neighbor balanced with minimal number of blocks at v(v–1)/2.

Keywords: BIB designs, BIBRC designs, Neighbor Balanced designs, µ-resolvable designs, AONBD, OLS and MOLS

RRJoST (2014)© STM Journals 2014. All Rights Reserved


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