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K.S. Kushwaha, C.M. Pandey, N.P.Singh, R. Ramesh, S.B.Barbuddhe
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K.S. Kushwaha
K.S. Kushwaha M.Sc., P.S.C.C., Ph.D.(Statistics) Recipient of Dr. Radha Krishnan Award (1992) Associate Professor (Statistics) Jawaharlal Nehru Krishi Vishwavidyalya Jabalpur, 482004, India

C.M. Pandey
C.M. Pandey M.Sc., Ph.D. (Statistics) Professor and Head Department of Biostatistics and Health Informatics Sanjay Gandhi Post Graduate Institute of Medical Sciences Lucknow - 226014, India

N.P.Singh is presently working as Director, ICAR Research Complex for Goa, Ela, Old Goa, Goa, India

R. Ramesh
R. Ramesh is a member of editorial board of the journal, Indian Phytopathology. He is presently working as Senior Scientist at ICAR Research Complex for Goa and his current areas of research are plant-pathogen interaction and plant disease management.

S.B.Barbuddhe is presently working as Senior Scientist at ICAR Research Complex for Goa and Project Coordinator of Centre of Excellence and Innovation in Biotechnology sponsored by Department of Biotechnology, Govt. of India on “Translational centre for molecular epidemiology of Listeria monocytogenes”.

The book is aimed at providing an understanding of basic principles and practices of Biostatistics. Attempt has been made to give a comprehensive inside into the basic concepts of biostatistics i.e. sound easy to read, relevant and useful to students and practitioners of biostatistics. The book includes the design of clinical trials and epidemiological studies collection of data, research methods, clinical measurement and sample size, calculations for various study designs. This makes it a handbook of biostatistics for students and researchers for agriculture, veterinary, life sciences, medicine, public health, biological and social sciences.

0 Start Pages

Preface   Now a days, National Eligibility Test (NET) has become an essential qualification to enter teaching profession in post graduate colleges, universities and other institution of higher learning as engineering, medical, basic, biological and social sciences etc. In NET, two qualifying quesion papers based on objective type questions have become necessary to clear with qualifying marks obtained before appearing in main examination. To make the examinees familiar with what type of objective questions are possible to be asked in examinations, an attempt has been made for gradual and systematic development of questions in “Biostatistics”. Two type of questions, e.g. (i) True/False and (ii) Multiple Choice Questions, have been developed along with their key answers in such a way that the subject matter can be easily and interestingly reachable to its readers and users. As the entire medical research in evolving towards evidence-based medical practice, medical literature is flooded with application of “Statistical Methods”. In medical sciences, any one who wishes to use biomedical literature should be able to comprehend the use and interpretation of statistical methods involved therein. This book is aimed to provide an understanding of basic principles and practices of “Biostatistics”. We have made an attempt to give a comprehensive inside into the basic concepts of biostatistics ie sound, easy to read, relevant and useful to students and practitioners of biostatistics. Our major objective is to motivate students and its readers to develop a positive and more critical attitude toward learning statistics. Our major objective is also to bridge the gap between theoretical and applied statistics, and introduce them to the realm of applied statistics. This book includes the design of clinical trials and epidemiological studies, collection of data, research methods, clinical measurement and sample size calculations for various study designs. This make it a hand book of biostatistics for students and researchers of medicine, public health nursing, paramedical sciences, biological and social sciences or in short anyone who encounters the use of biostatistics in his/her respective field. The authors are very much thankful and extend their honorable honour to Vice-Chancellor, J.N.K.V.V., Jabalpur and Director SGPGIMS, Lucknow for their kind permission to hand over the manuscript to NIPA, New Delhi for its publication. It is hoped that this book will help the students and researchers to develop interest and appreciation for the value of medical statistics. We look forward for constructive criticism from students and teachers so that the present book can further be improved to meet the requisite needs of the days.

1 Role of Statistics and Biostatistics in Health Sciences

True/False Q.1.    Statistics in singular is used to denote a subject (branch) of science. Q.2.    Statistics in plural is used to denote “data or methods” Q.3.    Statistics is defined as a science of collection, compilation, analysis and interpretation of numerical data. Q.4.    Statistics can be used for two major purposes: descriptive and infe-rential.

1 - 8 (8 Pages)
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2 Summarization and Presentation of Data

True/False   Q.1.    The set of observations or measurements collected on specific characteristics from each item (individual) constitutes data. Q.2.    Each characteristic that is measured or observed, varies from item to item and is called “Variable”. Q.3.    “Blood type”, “stage of disease” and “weight” observed on a group of cancer patients, are three distinct variables. Q.4.    A variable that can be expressed in numbers such as age, height, blood pressure, is said to be “Quantitative variable”.

9 - 20 (12 Pages)
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3 Probability

True/False Q.1.    A set containing all possible outcome of a trial in a study is known as “Sample space”. Q.2.    If we are interested in observing the blood type of a child born in a hospital then sample space may be a set S is of the form S = {A, B, AB, O}. Q.3.    If outcomes are continuous in nature, the sample space is specified as an interval that contains all possible outcome values. Q.4.    When the occurrence of one event excludes the occurrence of other events, the events are said to be “Mutually exclusive events”. Q.5.    In case of testing the type of blood of a newly born baby in a hospital, the blood types A, B, AB, O or gender (male, female) are exclusive events.

21 - 28 (8 Pages)
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4 Probability Distribution

True/False Q.1.    The set of all possible outcomes of a variable along with the frequency (the number of occurrence) of each outcome or a group of outcome is called “Frequency Distribution”. Q.2.    The frequency of an occurrence of each outcome of a trail divided by total frequency is known as “Relative frequency” of the outcome. Q.3.    The distribution of total probability “1” into probabilities of occurrence of each outcome of a trial, is known as probability distribution of the outcome.

29 - 40 (12 Pages)
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5 Sampling Methods

True/False Q.1.    Collectivity (totality) of all sampling units is known as the “Population” and population size is denoted by “N”. Q.2.    A list of all sampling units with their identification is known as “Sampling frame”. For example a list of all newly-born children in maternity home during a period of three months with specification of their sex, weight, name of their parents, their permanent address, etc. is known as sampling frame. Q.3.    A function of all sampling units in the population is known as population parameter or population constant.

41 - 52 (12 Pages)
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6 Theory of Estimation

True/False Q.1.    The process of knowing all the relevant information from the known sample to the unknown “Population parameter” is known as “Statistical inference.” Q.2.    The method of estimating the unknown parameter of the population on the basis of known sample values is known “Estimation method.” Q.3.    The “Point estimation and Interval estimation” are the two methods of estimating the unknown parameters of the population.

53 - 64 (12 Pages)
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7 Testing of Statistical Hypothesis

True/False Q.1.    A hypothesis that sets the fundamental objective of scientific study is called the “Research hypothesis”. Q.2.     A statistical assumption or statement about the unknown parameters of a population is known as Statistical hypothesis.

65 - 82 (18 Pages)
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8 Analysis of Variance and Multisample Comparison

True/False Q.1.    According to Prof. RA Fisher “ANOVA” is the separation of variance assignable to one group of causes from the variance assignable to other group of causes. Q.2.    The basic purpose of ANOVA technique is to test the equality (homogeneity) of several population means from the same  experiment.

83 - 100 (18 Pages)
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9 Hypothesis Testing for Categorical Data

True/False Q.1.    Qualitative or categorical data are frequently collected in medical investigation. Q.2.    Qualitative variables may be, e.g. sex, blood type, treatment, groups, classification of exposure or disease and patients survived or not. Q.3.    Qualitative variables include the grouped quantitative variables such as age groups of mothers, pre term babies, birth weight groups,  hypertensive or normotensive etc.

101 - 116 (16 Pages)
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10 Non Parametric Methods

True/False Q.1.    The most fundamental assumption for “Parametric inference” is that the random sample drawn is from “Normal” population. Q.2.    The most fundamental assumption of “Non-parametric” test is that the random sample drawn is from “Continuous distribution” Q.3.    The standard parametric methods are applicable for “Estimating the parameter” as well as for “Testing the hypothesis” about the parameters. Q.4.    Non-parametric methods, are applicable only for testing the hypothesis about  distribution but not applicable for estimation purpose of parameter.

117 - 132 (16 Pages)
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11 Simple Correlation and Regression

True/False Q.1.    Two independent random variables (X,Y) are always uncorrelated but reverse may not be true

133 - 148 (16 Pages)
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12 Epidemiological Study Designs and Analysis

True/False Q.1.    The purpose of most medical research is to identify the causes of disease and search out the ways to prevent or cure them. Q.2.    Now a day, epidemiology has become a basic science for public health Q.3.    The studies of diagnostics therapeutic and prognostic procedures have successfully incorporated into growing stream of “Clinical Epidemiology”.

149 - 162 (14 Pages)
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13 Clinical Trials

True/False Q.1.    In clinical practice and in public health, the objective is to find better ways to ‘prevent,  diagnose and treat disease’. Q.2.    Among all research designs, experimental study designs are the most reliable and  ideal designs to evaluate the ‘effectiveness or value’ of interventions (like drugs,  medication etc.) for human disease and disabilities.

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14 Diagnostic Tests

True /False Q.1.    A diagnostic test enables the doctors to reach at a decision whether the patient is suffering from a particular disease or not. Q.2.    The recent developments in the field by biotechnology have led to the development of many new medical tests. Q.3.    The general principles in designing and conduct diagnostic test studies are not known well.

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15 Survival Analysis

True/False Q.1.    In many epidemiological studies with substantial follow up time, it is very often an interest to study the time taken for a particular event to occur. Q.2.    The time taken for death or graft failure since transplant, time taken for relapse after treatment, time to death after treatment etc. are examples for survival time.

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16 Clinical Measurements

True/False Q.1.    The accuracy of the measurement refers to how close the measured value is to the true value. Q.2.    The precision refers to how close a set or group of measurements are together. Q.3.    If the processes of measurement are repeated under identical condition, then precision explains that up to what extent these repeated values are reliable.

191 - 196 (6 Pages)
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17 Demographic Methods and Vital Statistics

True/False Q.1.    Demographic data and vital statistics are important tools for researchers, epidemiologists, health planners and health professionals. Q.2.    The distribution of people across different geographic regions is known as population density.

197 - 206 (10 Pages)
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18 Applied Regression Analysis and Multivariate Methods

True/False Q.1.    In many clinical research studies, the regression analysis is used to develop models for prediction of an outcome from one or more explanatory variables. Q.2.    Now a days, the linear, logistic and Cox (proportional hazards) regression models are used frequently in medical research.

207 - 218 (12 Pages)
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19 Sample Sizes

True/False Q.1.    The precision of an estimator increases as the sample size increases. Q.2.    Statistical power is the probability that a statistical test will indicate a significant difference is true i.e. it is the probability of taking correct decision.

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20 End Pages

Bibliography Antonisamy, B., Salomon, C. and Samuel, P.P. (2009): Bio-statistics, Principles and Practice, Tata McGraw Hill Education Private Limited, New Delhi Fisher, R.A. (1947): The Design of Experiments, Oliver and Boyed, Edinburgh, 4th Edtion. Gupta, H.C. and Kapoor, V.K. (1990): Fundamental of Mathematical Statistics, S. Chand and Sons, New Delhi Kushwaha, K.S. and Kumar, Rajesh (2009): The Theory of Sample Surveys and Statistical Decision: First Edition, New India Publishing Agency, New Delhi. Kushwaha, K.S. and Kumar, Rajesh (2009): Basic Concepts in Statistics, First Edition, New India Publishing Agency, New Delhi. Kushwaha, K.S. (2011): Objective Agricultural Statistics, First Edition, New India Publishing Agency, New Delhi. Mood, A.M., Graybill, F.A. and Bose, D.D. (1974): Introduction to the Theory of Statistics, McGraw Hill Kogakusha Ltd., London. Murthy, M.N. (1977): Sampling Theory and Methods, Statistical Publishing Society, Kolkata. Steel, R.G.D. and Torre, J.H. (1980): Principles and Procedures of Statistics, A Biometrical Approach, 2nd Edition, McGraw Kogakusha Ltd, London. Snedekor, G.W. and Cochrom, W.G. (1989): Statistical Methods, Iowa State University Press, Ames, Iowa, U.S.A

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