**Basic Biostatistics: Statistics for Public Health Practice 2nd Edition by B. Burt Gerstman, ISBN-13: 978-1284036015**

[PDF eBook eTextbook]

- Publisher: Jones & Bartlett Learning; 2nd edition (February 21, 2014)
- Language: English
- 648 pages
- ISBN-10: 9781284036015
- ISBN-13: 978-1284036015

* Basic Biostatistics* is a concise, introductory text that covers biostatistical principles and focuses on the common types of data encountered in public health and biomedical fields. The text puts equal emphasis on exploratory and confirmatory statistical methods. Sampling, exploratory data analysis, estimation, hypothesis testing, and power and precision are covered through detailed, illustrative examples. The book is organized into three parts: Part I addresses basic concepts and techniques; Part II covers analytic techniques for quantitative response variables; and Part III covers techniques for categorical responses. The Second Edition offers many new exercises. With language, examples, and exercises that are accessible to students with modest mathematical backgrounds, this is the perfect introductory biostatistics text for undergraduates and graduates in various fields of public health. Features: Illustrative, relevant examples and exercises incorporated throughout the book. Answers to odd-numbered exercises provided in the back of the book. (Instructors may requests answers to even-numbered exercises from the publisher. Chapters are intentionally brief and limited in scope to allow for flexibility in the order of coverage. Equal attention is given to manual calculations as well as the use of statistical software such as StaTable, SPSS, and WinPepi.

**Table of Contents:**

Cover

Title Page

Copyright

Dedication

Contents

Preface

Acknowledgments

About the Author

Part I: General Concept and Techniques

Chapter 1 Measurement

1.1 What Is Biostatistics?

1.2 Organization of Data

1.3 Types of Measurement Scales

1.4 Data Quality

Chapter 2 Types of Studies

2.1 Surveys

2.2 Comparative Studies

Chapter 3 Frequency Distributions

3.1 Stemplots

3.2 Frequency Tables

3.3 Additional Frequency Charts

Chapter 4 Summary Statistics

4.1 Central Location: Mean

4.2 Central Location: Median

4.3 Central Location: Mode

4.4 Comparison of the Mean, Median, and Mode

4.5 Spread: Quartiles

4.6 Boxplots

4.7 Spread: Variance and Standard Deviation

4.8 Selecting Summary Statistics

Chapter 5 Probability Concepts

5.1 What Is Probability?

5.2 Types of Random Variables

5.3 Discrete Random Variables

5.4 Continuous Random Variables

5.5 More Rules and Properties of Probability

Chapter 6 Binomial Probability Distributions

6.1 Binomial Random Variables

6.2 Calculating Binomial Probabilities

6.3 Cumulative Probabilities

6.4 Probability Calculators

6.5 Expected Value and Variance of a Binomial Random Variable

6.6 Using the Binomial Distribution to Help Make Judgments About the Role of Chance

Chapter 7 Normal Probability Distributions

7.1 Normal Distributions

7.2 Determining Normal Probabilities

7.3 Finding Values that Correspond to Normal Probabilities

7.4 Assessing Departures from Normality

Chapter 8 Introduction to Statistical Inference

8.1 Concepts

8.2 Sampling Behavior of a Mean

8.3 Sampling Behavior of a Count and Proportion

Chapter 9 Basics of Hypothesis Testing

9.1 The Null and Alternative Hypotheses

9.2 Test Statistic

9.3 P-Value

9.4 Significance Level and Conclusion

9.5 One-Sample z-Test

9.6 Power and Sample Size

Chapter 10 Basics of Confidence Intervals

10.1 Introduction to Estimation

10.2 Confidence Intervals for μ When σ Is Known

10.3 Sample Size Requirements

10.4 Relationship Between Hypothesis Testing and Confidence Intervals

Part II: Quantitative Response Variable

Chapter 11 Inference About a Mean

11.1 Estimated Standard Error of the Mean

11.2 Student’s t-Distributions

11.3 One-Sample t-Test

11.4 Confidence Interval for μ

11.5 Paired Samples

11.6 Conditions for Inference

11.7 Sample Size and Power

Chapter 12 Comparing Independent Means

12.1 Paired and Independent Samples

12.2 Exploratory and Descriptive Statistics

12.3 Inference About the Mean Difference

12.4 Equal Variance t Procedure (Optional)

12.5 Conditions for Inference

12.6 Sample Size and Power

Chapter 13 Comparing Several Means (One-Way Analysis of Variance)

13.1 Descriptive Statistics

13.2 The Problem of Multiple Comparisons

13.3 Analysis of Variance (ANOVA)

13.4 Post Hoc Comparisons

13.5 The Equal Variance Assumption

13.6 Introduction to Rank-Based Tests

Chapter 14 Correlation and Regression

14.1 Data

14.2 Scatterplot

14.3 Correlation

14.4 Regression

Chapter 15 Multiple Linear Regression

15.1 The General Idea

15.2 The Multiple Linear Regression Model

15.3 Categorical Explanatory Variables in Regression Models

15.4 Regression Coefficients

15.5 ANOVA for Multiple Linear Regression

15.6 Examining Multiple Regression Conditions

Part III: Categorical Response Variable

Chapter 16 Inference About a Proportion

16.1 Proportions

16.2 The Sampling Distribution of a Proportion

16.3 Hypothesis Test, Normal Approximation Method

16.4 Hypothesis Test, Exact Binomial Method

16.5 Confidence Interval for a Population Proportion

16.6 Sample Size and Power

Chapter 17 Comparing Two Proportions

17.1 Data

17.2 Proportion Difference (Risk Difference)

17.3 Hypothesis Test

17.4 Proportion Ratio (Relative Risk)

17.5 Systematic Sources of Error

17.6 Power and Sample Size

Chapter 18 Cross-Tabulated Counts

18.1 Types of Samples

18.2 Describing Naturalistic and Cohort Samples

18.3 Chi-Square Test of Association

18.4 Test for Trend

18.5 Case–Control Samples

18.6 Matched Pairs

Chapter 19 Stratified Two-by-Two Tables

19.1 Preventing Confounding

19.2 Simpson’s Paradox

19.3 Mantel–Haenszel Methods

19.4 Interaction

Appendix A

Appendix B

Appendix C

Appendix D

Appendix E

Appendix F

Answers to Odd-Numbered Exercises

Index

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