Biostatistics - An Introduction

Description

Please Read Notes: Brand New, International Softcover Edition, Printed in black and white pages, minor self wear on the cover or pages, Sale restriction may be printed on the book, but Book name, contents, and author are exactly same as Hardcover Edition. Fast delivery through DHL/FedEx express. Cover Contents Foreword Preface Acknowledgements About the Author Chapter 1: Introduction to Statistics and its Biological Applications 1.1 Introduction 1.1.1 Sampling Methods 1.2 Is Statistics a Science? 1.3 Application of Statistics in Biology 1.3.1 P hases of the Statistical Decision-Making Process 1.4 Responsibility of the Decision Maker 1.5 Functions and Limitations of Statistics 1.5.1 Functions of Statistics 1.5.2 Limitations of Statistics 1.6 Distrust of Statistics 1.7 Nature of Statistical Law 1.7.1 Law of Statistical Regularity 1.7.2 Law of Inertia of Large numbers Exercises Answer the Questions Chapter 2: Data Structures, Data Sources and Data Collection 2.1 Introduction 2.2 Data Structures 2.2.1 Univariate Data 2.2.2 Bivariate Data 2.2.3 Multivariate Data 2.3 Data Sources 2.3.1 Primary Sources 2.3.2 Secondary Sources 2.3.3 Internal Source 2.3.4 External Source 2.3.5 Advantages and Disadvantages of Primary Data Over the Secondary Data 2.4 Data Collection 2.4.1 Survey Design 2.4.2 Pilot Survey of the Questionnaire 2.4.3 Editing Primary Data 2.4.4 Possible Errors in Secondary Data 2.4.5 Points to Be Considered While Using Secondary Data 2.4.6 Census and Sampling Methods Exercises Answer the Questions Chapter 3: Data Presentation 3.1 Introduction 3.2 Classification of Data 3.2.1 Types of Classification 3.3 Data Presentation 3.3.1 Textual Form 3.3.2 Tabular Form 3.3.3 Graphical Form 3.4 Types of Variables and Data 3.5 Levels of Measurement 3.5.1 Ratio Scale 3.5.2 Interval Scale 3.5.3 Ordinal Scale 3.5.4 Nominal Scale 3.6 Frequency 3.6.1 Frequency Distributions 3.7 Types of Class Interval 3.7.1 Exclusive Method 3.7.2 Inclusive Method 3.7.3 Open-end Method 3.8 Tally Mark 3.9 Construction of a Discrete Frequency Distribution 3.10 Construction of a Continuous Frequency Distribution 3.11 Cumulative and Relative Frequencies 3.11.1 Cumulative Frequency 3.11.2 Relative Frequency 3.12 Diagrammatic Representation of Data 3.12.1 A dvantages and Disadvantages of Diagrammatic Representation 3.12.2 T ypes of Diagrams Exercises Answer the Questions Chapter 4: Measures of Central Tendency 4.1 Introduction 4.2 Measures of Central Tendency 4.2.1 Properties of Best Average 4.3 Arithmetic Mean 4.3.1 Discrete Data 4.3.2 Discrete Data with Frequency 4.3.3 Continuous Data with Frequency 4.4 Mathematical Properties of Arithmetic Mean 4.4.1 Disadvantages of Arithmetic Mean Related to Other Averages 4.5 Median 4.5.1 Discrete Data 4.5.2 Discrete Data with Frequency 4.5.3 Continuous Data with Frequency 4.5.4 Graphical Method to Find the Median 4.6 Quartiles, Deciles and Percentiles 4.7 Mode 4.7.1 Discrete Data 4.7.2 Discrete Data with Frequency 4.7.3 Continuous Data with Frequency 4.7.4 Graphical Method to Evaluate the Mode 4.8 Comparison of Mean, Median and Mode 4.9 Weighted Arithmetic Mean 4.9.1 Advantages of the Weighted Mean 4.10 Geometric Mean 4.11 Harmonic Mean Exercises Answer the Questions Chapter 5: Dispersion 5.1 Introduction 5.2 Range 5.2.1 Merits 5.2.2 Demerits 5.3 Quartile Deviation 5.3.1 Merits 5.3.2 Demerits 5.4 Coefficient of Quartile Dispersion 5.5 Mean Deviation 5.5.1 Discrete Series 5.5.2 Distribution with Frequency 5.6 Standard Deviation 5.7 Relative Measures of Dispersion 5.7.1 Coefficient of Variation 5.7.2 Coefficient of Quartile Deviation Exercises Answer the Questions Chapter 6: Skewness, Moments and Kurtosis 6.1 Introduction 6.2 Dispersion and Skewness 6.3 Moments 6.4 Kurtosis Exercises Answer the Questions Chapter 7: Correlation and Regression Analysis 7.1 Introduction 7.2 Correlation 7.2.1 Simple Correlation/Correlation 7.2.2 Rank Correlation 7.2.3 Group Correlation 7.2.4 Assumptions for Karl Pearson’s Coefficient of Correlation 7.2.5 Limitations of Correlation 7.2.6 Properties of Correlation 7.2.7 Scatter Diagram 7.3 Karl Pearson’s Coefficient of Correlation 7.4 Coefficient of Correlation for a Grouped Data 7.5 Probable Error of the Coefficient of Correlation 7.6 Rank Correlation 7.7 Regression Equations 7.7.1 Regression 7.7.2 Regression Equation Y depends on X Exercises Answer the Questions Chapter 8: Probability 8.1 Introduction 8.2 Definition for Certain Key Terms 8.3 Meaning of Probability 8.3.1 Addition Rules for Probability 8.3.2 Addition Theorem on Probability 8.3.3 Multiplication Rule on Probability When Events Are Independent 8.4 Baye’s Theorem Exercises Answer the Questions Chapter 9: Random Variables and Expectation 9.1 Introduction 9.2 Random Variable 9.2.1 Discrete Random Variable 9.2.2 Continuous Random Variable 9.3 Probability Distribution 9.3.1 Discrete Probability Distribution 9.3.2 Characteristics of a Discrete Probability Distribution 9.3.3 Probability Function 9.4 Mathematical Expectation 9.5 Mean of a Random Variable 9.6 Standard Results 9.7 Variance of a Random Variable Exercises Answer the Questions Chapter 10: Discrete Probability Distribution [Binomial and Poisson Distributions] 10.1 Introduction 10.2 Binomial Distribution 10.2.1 Characteristics of a Bernoulli Process 10.2.2 Definition of Binomial Distribution 10.2.3 Conditions of Binomial Distribution 10.2.4 Properties of Binomial Distributions 10.2.5 Mean of Binomial Distribution 10.2.6 Variance of Binomial Distribution 10.3 Poisson Distribution 10.3.1 Definition of Poisson Distribution 10.3.2 Properties of Poisson Distribution 10.3.3 Mean of the Poisson Distribution 10.3.4 Variance of the Poisson Distribution Exercises Answer the Questions Chapter 11: Continuous Probability Distribution [Normal Distribution] 11.1 Introduction 11.2 Definition of Normal Distribution 11.3 Standard Normal Distribution 11.4 Properties of Normal Distribution Exercises Answer the Questions Chapter 12: Theory of Sampling 12.1 Introduction 12.2 Why Sample? 12.3 How to Choose It? 12.4 Sample Design 12.5 Key Words and Notations 12.6 Advantages and Disadvantages of Sampling 12.7 Non Random Errors/Non Sampling Errors 12.8 Random Errors/Sampling Errors 12.9 Types of Sample 12.9.1 Probability Sample 12.9.2 Non-probability Sample 12.10 Random Sampling 12.10.1 Systematic Sampling 12.10.2 Stratified Sampling 12.10.3 Multi-stage Sampling 12.11 Non-Random Sampling Methods 12.11.1 Convenience Sampling 12.11.2 Purposive Sampling 12.11.3 Quota Sampling 12.11.4 Cluster Sampling 12.11.5 Sequential Sampling 12.12 Sampling Distributions 12.13 Need for Sampling Distribution 12.14 Standard Error for Different Situations 12.14.1 When the Population Size Infinite 12.14.2 When the Population Size is Finite 12.14.3 Sampling Distribution Based on Sample Means 12.15 Point and Internal Estimation 12.15.1 Point Estimate 12.15.2 Properties of Good Point Estimators 12.16 Interval Estimate 12.17 Confidence Interval Estimation for Large Samples 12.18 Confidence Intervals for Difference between Means 12.19 Estimating a Population Proportion 12.20 Estimating the interval based on difference between two proportions 12.21 Confidence Interval Estimation for Small Sample 12.22 Determining the Sample Size Exercises Answer the Questions Chapter 13: Hypothesis Testing/Parametric Tests/Distribution Tests/Tests of Significance 13.1 Introduction 13.2 Null Hypothesis [H0] 13.3 Alternative Hypothesis [H1] 13.4 Type I and Type II Errors 13.5 Meaning of Parametric and Non-Parametric Test 13.5.1 Parametric Test 13.5.2 Non-parametric Test 13.6 Selection of Appropriate Test – Statistic 13.7 Methodology of Statistical Testing 13.8 Test for a Specified Mean – Large Sample 13.9 Test for Equality of Two Populations – Large Sample 13.10 Test for Population Proportion – Large Sample 13.11 Test for Equality of Two Proportions – Large Samples 13.12 Test for Equality of Two Standard Deviations – Large Samples 13.13 Student’s t-distribution 13.14 Properties of t-distribution 13.15 Test for Specified Mean [Small Sample] 13.16 Test for Equality of Two Population Means – Small Samples [s1 and s2 are not known] 13.17 Paired t-test for Difference of Mean 13.18 Chi-square Distribution 13.18.1 Chi-square Test 13.18.2 Test for Goodness of Fit 13.18.3 Tests for Independence of Attributes 13.18.4 Whenever the Expected Frequencies of the Cell Entries are Less than 5 13.18.5 Test for a Specified Population Variance 13.19 Snedecor’s F-distribution 13.19.1 Test for Difference of Two Population’s Variance 13.20 Analysis of Variance [ANOVA] 13.20.1 One Way Classification 13.20.2 Two Way Classification Exercises Answer the Questions Appendix A Appendix B Index