Biostatistics

Biostatistics

Released January 2013
Publisher(s): Pearson India
ISBN: 9789332513921

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Book description

Biostatistics is exclusively designed for the undergraduate students of Botany, Biotechnology and Zoology for gaining fundamental knowledge on biostatistics and its applications. Adequate coverage has been provided to the concepts of biostatistics making this book useful in biological data management.

Table of contents

  1. Cover
  2. Title Page
  3. Contents
  4. About the Author
  5. Dedication
  6. Foreword
  7. Preface
  8. Chapter 1: Introduction to Statistics and Its Biological Applications
    1. 1.1 Introduction
      1. 1.1.1 Sampling Methods
    2. 1.2 Is Statistics a Science?
    3. 1.3 Application of Statistics in Biology
      1. 1.3.1 Phases of the Statistical Decision-Making Process
    4. 1.4 Responsibility of the Decision Maker
    5. 1.5 Functions and Limitations of Statistics
      1. 1.5.1 Functions of Statistics
      2. 1.5.2 Limitations of Statistics
    6. 1.6 Distrust of Statistics
    7. 1.7 Nature of Statistical Law
      1. 1.7.1 Law of Statistical Regularity
      2. 1.7.2 Law of Inertia of Large Numbers
    8. Exercises
    9. Answer the Questions
  9. Chapter 2: Data Structures, Data Sources and Data Collection
    1. 2.1 Introduction
    2. 2.2 Data Structures
      1. 2.2.1 Univariate Data
      2. 2.2.2 Bivariate Data
      3. 2.2.3 Multivariate Data
    3. 2.3 Data Sources
      1. 2.3.1 Primary Sources
      2. 2.3.2 Secondary Sources
      3. 2.3.3 Internal Source
      4. 2.3.4 External Source
      5. 2.3.5 Advantages and Disadvantages of Primary Data Over the Secondary Data
    4. 2.4 Data Collection
      1. 2.4.1 Survey Design
      2. 2.4.2 Pilot Survey of the Questionnaire
      3. 2.4.3 Editing Primary Data
      4. 2.4.4 Possible Errors in Secondary Data
      5. 2.4.5 Points to Be Considered While Using Secondary Data
      6. 2.4.6 Census and Sampling Methods
    5. Exercises
    6. Answer the Questions
  10. Chapter 3: Data Presentation
    1. 3.1 Introduction
    2. 3.2 Classification of Data
      1. 3.2.1 Types of Classification
    3. 3.3 Data Presentation
      1. 3.3.1 Textual Form
      2. 3.3.2 Tabular Form
      3. 3.3.3 Graphical Form
    4. 3.4 Types of Variables and Data
    5. 3.5 Levels of Measurement
      1. 3.5.1 Ratio Scale
      2. 3.5.2 Interval Scale
      3. 3.5.3 Ordinal Scale
      4. 3.5.4 Nominal Scale
    6. 3.6 Frequency
      1. 3.6.1 Frequency Distributions
    7. 3.7 Types of Class Interval
      1. 3.7.1 Exclusive Method
      2. 3.7.2 Inclusive Method
      3. 3.7.3 Open-end Method
    8. 3.8 Tally Mark
    9. 3.9 Construction of a Discrete Frequency Distribution
    10. 3.10 Construction of a Continuous Frequency Distribution
    11. 3.11 Cumulative and Relative Frequencies
      1. 3.11.1 Cumulative Frequency
      2. 3.11.2 Relative Frequency
    12. 3.12 Diagrammatic Representation of Data
      1. 3.12.1 Advantages and Disadvantages of Diagrammatic Representation
      2. 3.12.2 Types of Diagrams
    13. Exercises
    14. Answer the Questions
  11. Chapter 4: Measures of Central Tendency
    1. 4.1 Introduction
    2. 4.2 Measures of Central Tendency
      1. 4.2.1 Properties of Best Average
    3. 4.3 Arithmetic Mean
      1. 4.3.1 Discrete Data
      2. 4.3.2 Discrete Data with Frequency
      3. 4.3.3 Continuous Data with Frequency
    4. 4.4 Mathematical Properties of Arithmetic Mean
      1. 4.4.1 Disadvantages of Arithmetic Mean Related to Other Averages
    5. 4.5 Median
      1. 4.5.1 Discrete Data
      2. 4.5.2 Discrete Data with Frequency
      3. 4.5.3 Continuous Data with Frequency
      4. 4.5.4 Graphical Method to Find the Median
    6. 4.6 Quartiles, Deciles and Percentiles
    7. 4.7 Mode
      1. 4.7.1 Discrete Data
      2. 4.7.2 Discrete Data with Frequency
      3. 4.7.3 Continuous Data with Frequency
      4. 4.7.4 Graphical Method to Evaluate the Mode
    8. 4.8 Comparison of Mean, Median and Mode
    9. 4.9 Weighted Arithmetic Mean
      1. 4.9.1 Advantages of the Weighted Mean
    10. 4.10 Geometric Mean
    11. 4.11 Harmonic Mean
    12. Exercises
    13. Answer the Questions
  12. Chapter 5: Dispersion
    1. 5.1 Introduction
    2. 5.2 Range
      1. 5.2.1 Merits
      2. 5.2.2 Demerits
    3. 5.3 Quartile Deviation
      1. 5.3.1 Merits
      2. 5.3.2 Demerits
    4. 5.4 Coefficient of Quartile Dispersion
    5. 5.5 Mean Deviation
      1. 5.5.1 Discrete Series
      2. 5.5.2 Distribution with Frequency
    6. 5.6 Standard Deviation
    7. 5.7 Relative Measures of Dispersion
      1. 5.7.1 Coefficient of Variation
      2. 5.7.2 Coefficient of Quartile Deviation
    8. Exercises
    9. Answer the Questions
  13. Chapter 6: Skewness, Moments and Kurtosis
    1. 6.1 Introduction
    2. 6.2 Dispersion and Skewness
    3. 6.3 Moments
    4. 6.4 Kurtosis
    5. Exercises
    6. Answer the Questions
  14. Chapter 7: Correlation and Regression Analysis
    1. 7.1 Introduction
    2. 7.2 Correlation
      1. 7.2.1 Simple Correlation/Correlation
      2. 7.2.2 Rank Correlation
      3. 7.2.3 Group Correlation
      4. 7.2.4 Assumptions for Karl Pearson’s Coefficient of Correlation
      5. 7.2.5 Limitations of Correlation
      6. 7.2.6 Properties of Correlation
      7. 7.2.7 Scatter Diagram
    3. 7.3 Karl Pearson’s Coefficient of Correlation
    4. 7.4 Coefficient of Correlation for a Grouped Data
    5. 7.5 Probable Error of the Coefficient of Correlation
    6. 7.6 Rank Correlation
    7. 7.7 Regression Equations
      1. 7.7.1 Regression
      2. 7.7.2 Regression Equation Y depends on X
    8. Exercises
    9. Answer the Questions
  15. Chapter 8: Probability
    1. 8.1 Introduction
    2. 8.2 Definition for Certain Key Terms
    3. 8.3 Meaning of Probability
      1. 8.3.1 Addition Rules for Probability
      2. 8.3.2 Addition Theorem on Probability
      3. 8.3.3 Multiplication Rule on Probability When Events Are Independent
      4. 8.3.4 Compound Probability or Conditional Probability
    4. 8.4 Baye’s Theorem
    5. Exercises
    6. Answer the Questions
  16. Chapter 9: Random Variables and Expectation
    1. 9.1 Introduction
    2. 9.2 Random Variable
      1. 9.2.1 Discrete Random Variable
      2. 9.2.2 Continuous Random Variable
    3. 9.3 Probability Distribution
      1. 9.3.1 Discrete Probability Distribution
      2. 9.3.2 Characteristics of a Discrete Probability Distribution
      3. 9.3.3 Probability Function
    4. 9.4 Mathematical Expectation
    5. 9.5 Mean of a Random Variable
    6. 9.6 Standard Results
    7. 9.7 Variance of a Random Variable
    8. Exercises
    9. Answer the Questions
  17. Chapter 10: Discrete Probability Distribution [Binomial and Poisson Distributions]
    1. 10.1 Introduction
    2. 10.2 Binomial Distribution
      1. 10.2.1 Characteristics of a Bernoulli Process
      2. 10.2.2 Definition of Binomial Distribution
      3. 10.2.3 Conditions of Binomial Distribution
      4. 10.2.4 Properties of Binomial Distributions
      5. 10.2.5 Mean of Binomial Distribution
      6. 10.2.6 Variance of Binomial Distribution
    3. 10.3 Poisson Distribution
      1. 10.3.1 Definition of Poisson Distribution
      2. 10.3.2 Properties of Poisson Distribution
      3. 10.3.3 Mean of the Poisson Distribution
      4. 10.3.4 Variance of the Poisson Distribution
    4. Exercises
    5. Answer the Questions
  18. Chapter 11: Continuous Probability Distribution
    1. 11.1 Introduction
    2. 11.2 Definition of Normal Distribution
    3. 11.3 Standard Normal Distribution
    4. 11.4 Properties of Normal Distribution
    5. Exercises
    6. Answer the Questions
  19. Chapter 12: Theory of Sampling
    1. 12.1 Introduction
    2. 12.2 Why Sample?
    3. 12.3 How to Choose It?
    4. 12.4 Sample Design
    5. 12.5 Key Words and Notations
    6. 12.6 Advantages and Disadvantages of Sampling
    7. 12.7 Non Random Errors/Non Sampling Errors
    8. 12.8 Random Errors/Sampling Errors
    9. 12.9 Types of Sample
      1. 12.9.1 Probability Sample
      2. 12.9.2 Non-probability Sample
    10. 12.10 Random Sampling
      1. 12.10.1 Systematic Sampling
      2. 12.10.2 Stratified Sampling
      3. 12.10.3 Multi-stage Sampling
    11. 12.11 Non-Random Sampling Methods
      1. 12.11.1 Convenience Sampling
      2. 12.11.2 Purposive Sampling
      3. 12.11.3 Quota Sampling
      4. 12.11.4 Cluster Sampling
      5. 12.11.5 Sequential Sampling
    12. 12.12 Sampling Distributions
    13. 12.13 Need for Sampling Distribution
    14. 12.14 Standard Error for Different Situations
      1. 12.14.1 When the Population Size Infinite
      2. 12.14.2 When the Population Size is Finite
      3. 12.14.3 Sampling Distribution Based on Sample Means
    15. 12.15 Point and Internal Estimation
      1. 12.15.1 Point Estimate
      2. 12.15.2 Properties of Good Point Estimators
    16. 12.16 Interval Estimate
    17. 12.17 Confidence Interval Estimation for Large Samples
    18. 12.18 Confidence Intervals for Difference Between Means
    19. 12.19 Estimating a Population Proportion
    20. 12.20 Estimating the Interval Based on Difference Between Two Proportions
    21. 12.21 Confidence Interval Estimation for Small Sample
    22. 12.22 Determining the Sample Size
    23. Exercises
    24. Answer the Questions
  20. Chapter 13: Hypothesis Testing/Parametric Tests/Distribution Tests/Tests of Significance
    1. 13.1 Introduction
    2. 13.2 Null Hypothesis [H0]
    3. 13.3 Alternative Hypothesis [H1]
    4. 13.4 Type I and Type II Errors
    5. 13.5 Meaning of Parametric and Non-Parametric Test
      1. 13.5.1 Parametric Test
      2. 13.5.2 Non-parametric Test
    6. 13.6 Selection of Appropriate Test – Statistic
    7. 13.7 Methodology of Statistical Testing
    8. 13.8 Test for a Specified Mean – Large Sample
    9. 13.9 Test for Equality of Two Populations – Large Sample
    10. 13.10 Test for Population Proportion – Large Sample
    11. 13.11 Test for Equality of Two Proportions – Large Samples
    12. 13.12 Test for Equality of Two Standard Deviations – Large Samples
    13. 13.13 Student’s t-Distribution
    14. 13.14 Properties of t-Distribution
    15. 13.15 Test for Specified Mean [Small Sample]
    16. 13.16 Test for Equality of Two Population Means – Small Samples [σ1 and σ2 are not known]
    17. 13.17 Paired t-Test for Difference of Mean
    18. 13.18 Chi-square Distribution
      1. 13.18.1 Chi-square Test
      2. 13.18.2 Test for Goodness of Fit
      3. 13.18.3 Tests for Independence of Attributes
      4. 13.18.4 Whenever the Expected Frequencies of the Cell Entries are Less than 5
      5. 13.18.5 Test for a Specified Population Variance
    19. 13.19 Snedecor’s F-Distribution
      1. 13.19.1 Test for Difference of Two Population’s Variance
    20. 13.20 Analysis of Variance [ANOVA]
      1. 13.20.1 One Way Classification
      2. 13.20.2 Two Way Classification
    21. Exercises
    22. Answer the Questions
  21. Appendix A
  22. Appendix B
  23. Acknowledgements
  24. Copyright
  25. Back Cover

Product information

  • Title: Biostatistics
  • Author(s):
  • Release date: January 2013
  • Publisher(s): Pearson India
  • ISBN: 9789332513921