# Basic Biostatistics: Statistics for Public Health Practice / Edition 1

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… See more details below

## Overview

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.

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.

## Product Details

ISBN-13:
9780763735807
Publisher:
Jones & Barlett Learning
Publication date:
01/28/2008
Edition description:
1E
Pages:
557
Product dimensions:
5.90(w) x 8.90(h) x 1.30(d)

## Related Subjects

Preface     xi
Acknowledgments     xv
General Concept and Techniques
Measurement     1
What Is Biostatistics?     1
Organization of Data     2
Types of Measurements     5
Data Quality     7
Types of Studies     15
Surveys     15
Comparative Studies     21
Frequency Distributions     35
Stemplots     35
Frequency Tables     51
Summary Statistics     63
Central Location: Mean     63
Central Location: Median     67
Central Location: Mode     70
Comparison of the Mean, Median, and Mode     70
Boxplots     75
Spread: Variance and Standard Deviation     78
Selecting Summary Statistics     84
Probability Concepts     89
What Is Probability?     89
Types of Random Variables     92
Discrete Random Variables     93
Continuous Random Variables     100
More Rules and Properties of Probability     105
Binomial Probability Distributions     115
Binomial Random Variables     115
Calculating Binomial Probabilities     116
Cumulative Probabilities     119
Probability Calculators     120
Expected Value and Variance of a Binomial Random Variable     123
Using the Binomial Distribution to Help Make Judgments     125
Normal Probability Distributions     129
Normal Distributions     129
Determining Normal Probabilities     139
Finding Values That Correspond to Normal Probabilities     145
Assessing Departures from Normality     147
Introduction to Statistical Inference     155
Concepts     155
Sampling Behavior of a Mean     158
Sampling Behavior of a Count and Proportion     167
Basics of Hypothesis Testing     175
The Null and Alternative Hypotheses     175
Test Statistic     178
P-Value     181
Significance Level     182
One-Sample z Test     184
Power and Sample Size     188
Basics of Confidence Intervals     197
Introduction to Estimation     197
Confidence Interval for [mu] When [sigma] Known      199
Sample Size Requirements     203
Relationship Between Hypothesis Testing and Confidence Intervals     205
Quantitative Response Variable
Estimated Standard Error of the Mean     209
Student's t Distributions     210
One-Sample t Test     214
Confidence Interval for [mu]     217
Paired Samples     218
Conditions for Inference     224
Sample Size and Power     226
Comparing Independent Means     235
Paired and Independent Samples     235
Exploratory and Descriptive Statistics     239
Inference About the Mean Difference     243
Equal Variance t Procedure (Optional)     247
Conditions for Inference     248
Sample Size and Power     250
Comparing Several Means (One-Way ANOVA)     259
Descriptive Statistics     260
The Problem of Multiple Comparisons     265
Analysis of Variance (ANOVA)     266
Post Hoc Comparisons     276
The Equal Variance Assumption     282
Introduction to Non-Parametric Tests     287
Correlation and Regression     295
Data      295
Scatterplots     296
Correlation     299
Regression     311
Multiple Linear Regression     333
The General Idea     333
The Multiple Linear Regression Model     334
Categorical Explanatory Variables in Regression Models     337
Regression Coefficients     340
ANOVA for Multiple Linear Regression     342
Examining Multiple Regression Conditions     346
Categorical Response Variable
Proportions     349
The Sampling Distribution of a Proportion     352
Hypothesis Test, Normal Approximation     354
Hypothesis Test, Exact Binomial Method     357
Confidence Interval for a Population Proportion     363
Sample Size and Power     366
Comparing Two Proportions     373
Data     373
Proportion Difference (Risk Difference)     375
Hypothesis Test     380
Proportion Ratio (Relative Risk)     389
Systematic Sources of Error     393
Power and Sample Size     396
Cross-Tabulated Counts     407
Types of Samples     407
Describing Naturalistic and Cohort Samples     409
Chi-Square Test of Association     421
Test for Trend     431
Case-Control Samples     436
Matched Pairs     446
Stratified 2-by-2 Tables     465
Preventing Confounding     465
Mantel-Haenszel Methods     468
Interaction     474
Table of 2000 Random Digits     483
z Table. Cummulative Probabilities for a Standard Normal Random Variable     485
t Table     487
F Table     489
X[superscript 2] Table     493
Two-Tails of z     495
Answers to Odd Numbered Exercises     497
Index     547