by T Pullaiah, B Ravindra Reddy, KLAP Sarma
Imprint : Daya Publishing House
Year : 2021
Price : Rs. 8495.00
Biblio : ix+228p.,figs.,tabls., 25 cm
Prof. K.L.A.P Sarma, is working as Professor and Head, Department of Statistics, Sri Krishnadevaraya University, Anantapuram – 515 003 since 1981. Born on 17-5-1953, Prof. Sarma worked as Chairman, BOS for 9 years and having 32 years of teaching experience of Micro-biology and Sericulture coureses. He has guided 8 M.Phil. candidates and 12 Ph.D. candidates successfully and 3 more candidates are presently working for Ph.D. degree.<br/> <BR> Dr. B. Ravindra Reddy is Assistant Professor of Statistics & Mathematics in the Department of Statistics and Mathematics, S.V. Agricultural College, Acharya N.G. Ranga Agricultural University, Tirupati (A.P) where he has been involved in the activities of teaching and research since 2006.<br/> <BR> Dr. T. Pullaiah, Professor, Department of Botany, Sri Krishnadevaraya University, Anantpur. Besides this, he held several positions in the university which include Dean, Head of the Department, Member of Species Survival Commission on International Union for Conservation of Nature (IUCN) and Natural Resources.
About The Book
The book 'Biostatistics' consists of ten chapters explaining statistical tools used in analyzing biological, biomedical and biochemical experimental data. Statistical tools, techniques and methods are explained with many real life problems and special care is taken to explain mathematical formulae and calculations keeping in view that the readers are non-mathematical students who are not having much mathematical background. <BR> The book mainly concentrates on (1) Collection, classification and tabulation of data, (2) Presentation of Data (both diagrammatic and graphical repreentation) <BR> (3) Analysis and (4) Inference (both estimation of parameters and testing of hypotheses). Most popularly used DMR test, by any biological students is also discussed along with its applications. At the end of each chapter, self assessment questions are given. This book can also be used by civil, mechanical, electrical and computer engineers in analyzing their experimental data and to take statistically valid decisions.
Table of Contents
1. Introduction to Biostatistics 1-14 <BR> 1.1. Need for decision making (DM) 1 <BR> 1.2. Basic concepts 3 <BR> 1.3. Sampling techniques 7 <BR> 1.4. Simple random sampling (SRS) 8 <BR> 1.5. Stratified random sampling (StRS) 10 <BR> 1.6. Systematic sampling (SyS) 11 <BR> Review questions and problems 12 <BR> References 14<br/> <BR> 2. Collection, classification and tabulation of data 15-26 <BR> 2.1. Introduction to collection of data 15 <BR> 2.2. Editing of data 16 <BR> 2.3. Classification of data 17 <BR> 2.4. Tabulation 18 <BR> 2.5. Frequency tables 21 <BR> Review questions and problems 23 <BR> References 26<br/> <BR> 3. Presentation of data 27-55 <BR> 3.1. Introduction 27 <BR> 3.2. Diagrammatic representation of data 27 <BR> 3.3. Graphical representation of data 39 <BR> 3.4. Graphs for frequency distributions 41 <BR> 3.5. Graphs for time series 48 <BR> 3.6. Range graphs 51 <BR> Review questions and problems 52 <BR> References 55<br/> <BR> 4. Different statistical measures 56-88 <BR> 4.1. Introduction 56 <BR> 4.2. Measures of central tendencies 56 <BR> 4.3. Measures of variation or dispersion 72 <BR> 4.4. Coefficient of Variation 79 <BR> 4.5. Skewness 80 <BR> 4.6. Kurtosis 84 <BR> Review questions and problems 85 <BR> References 88<br/> <BR> 5. Probability 89-100 <BR> 5.1. Introduction 89 <BR> 5.2. Basic concepts and notations 89 <BR> 5.3. Definitions of probability 91 <BR> 5.4. Theorems on probability 95 <BR> 5.5. Conditional probability and <BR> multiplication theorem 96 <BR> 5.6. Properties and Utilities of Probability 97 <BR> Review questions and problems 98 <BR> References 100<br/> <BR> 6. Probability distributions 101-122 <BR> 6.1. Introduction 101 <BR> 6.2. Random variable 102 <BR> 6.3. Binomial distribution 104 <BR> 6.4. Poisson distribution 107 <BR> 6.5. Normal distribution 111 <BR> 6.6. Exponential distribution 118 <BR> Review questions and problems 119 <BR> References 122<br/> <BR> 7. Correlation and regression analysis 123-147 <BR> 7.1. Introduction to correlation and regression analysis 123 <BR> 7.2.Scatter diagram method 125 <BR> 7.3.Karl Pearson’s method 128 <BR> 7.4.Spearman’s method 131 <BR> 7.5. Regression lines and regression coefficients 136 <BR> 7.6. Fitting of regression lines 139 <BR> Review questions and problems 145 <BR> References 147<br/> <BR> 8. Testing of Hypothesis-Large Sample Tests 148-167 <BR> 8.1.Introduction to testing of hypotheses 148 <BR> 8.2. Some fundamental definitions and concepts used <BR> in testing of hypothesis 149 <BR> 8.3. Large sample test procedure 154 <BR> 8.4. Tests for Proportions 154 <BR> 8.5. Tests for means 160 <BR> 8.6. Test the significant difference between two sample <BR> standard deviations (S.D.’s) 162 <BR> Review questions and problems 164 <BR> References 167<br/> <BR> 9. Testing of Hypotheses-Small Sample Tests 168-195 <BR> 9.1. Introduction 168 <BR> 9.2. Ch