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

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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