Applied Statistics in Occupational Safety and Health

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Applied Statistics in Occupational Safety and Health, Third Edition, provides occupational safety and health professionals with an introductory guide to basic statistics and data analysis. This book is written in an easy-to-understand format with step-by-step procedures to analyze data using a variety of statistical techniques. This third edition includes new examples and numerous updates. Topics in this book include statistical procedures, descriptive statistical methods, correlations, regression, and non-parametric statistical tests. Each chapter presents sample problems and solutions.

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Contents List of Figures and Tables Preface About the Author 1 Fundamentals of Statistics Statistics and Their Use in Safety Statistics Defined Common Terms and Notations Quantitative and Qualitative Data Statistical Notations Research Questions and Hypotheses Types of Studies Retrospective Studies Prospective Studies Experiments Statistical Samples versus Statistical Populations Bias Probability Sample Selection Procedures Sampling Techniques Random Samples Simple Random Samples Cluster Samples Stratified Random Samples Nonprobability Sample Selection Procedures Chunk Sampling Volunteer Samples Variables Dependent and Independent Variables Chapter Summary Chapter Review Exercises 2 Probability and Chance Probability Marginal Probabilities Joint Event Probabilities Union Probabilities Conditional Probabilities Factorials, Permutations, Ordered Combinations, and Combinations Factorials Permutations Combinations Binomial Probabilities Poisson Probability Chapter Summary Chapter Review Exercises 3 Distributions Statistical Distributions and Populations Frequencies Histograms Frequency Polygons Percentages, Cumulative Percentages, and Percentiles Normal Distribution Binomial Distribution t Distribution Chi-square Distribution F Distribution Chapter Summary Chapter Review Exercises 4 Descriptive Statistics Data Formats Categorical Data Ordinal Data Interval Data Ratio Data Strength of the Data Formats Measures of Central Tendency Mean Median Mode Measures of Variability Range Variance Standard Deviation Interquartile Range z Scores z Scores and Percentages of the Population Confidence Intervals for Means 95% Confidence Intervals 99% Confidence Intervals Interpreting Confidence Intervals Chapter Summary Chapter Review Exercises 5 Statistical Tests Statistical Hypotheses Inferential Statistical Testing Type I and Type II Errors Alpha Levels Statistical Power of a Test Inferential Statistics Test Procedure Developing a Statistical Hypothesis Choosing the Appropriate Statistical Test or Procedure Determining the Statistical Distribution Determining Significance Levels Formulating a Decision Rule Running the Test Formulating a Conclusion and Making a Decision Chapter Summary Chapter Review Exercises 6 Inferential Statistics for Means z-Test Comparing a Sample Mean to a Known Population Mean Test Assumptions Hypothesis Construction Determine Significance Levels Using a z Table Formulate a Decision Rule z Test Formula Conclusions Example z Test Problem Independent Samples z-Test Test Assumptions Independent Samples z-Test Formula Example Independent Samples z-test Problem Hypothesis Construction Conclusions Example z Test Problem t -Test for a Single Mean Test Assumptions Hypothesis Construction t Test Hypotheses Determine Significance Levels Formulate a Decision Rule t-Test Formula for a Single Mean Conclusions Example t-Test Problem t-Test for Independent Samples Paired Samples t-Tests Test Assumptions Hypothesis Construction Determine Significance Levels Formulate a Decision Rule Test Formula Conclusions Example Paired Samples t-Test Problem One-way Analysis of Variance Procedure Assumptions Hypothesis Construction Procedure Formulas Hypothesis Construction Formulate a Decision Rule Calculate F Ratio Conclusions Post Hoc Procedures Tukey's HSD Calculate Tukey's HSD Formulate a Decision Rule Example ANOVA Problem Formulate a Decision Rule Calculate F ratio Conclusions Run Post Hoc Tests Chapter Summary Chapter Review Exercises 7 Correlation and Regression Correlation Pearson Correlation Coefficient Assumptions Pearson Correlation Coefficient Formula Sample Problem Significance Testing for Correlation Coefficients Test Hypotheses Test Formula Sample Problem Spearman Rank-Order Correlation Coefficient Assumptions Spearman Rank-Order Correlation Coefficient Formula Sample Problem Phi Coefficient Assumptions Phi Coefficient Formula Sample Problem Point Biserial Correlation Assumptions Point Biserial Correlation Formula Sample Problem Significance Testing for Correlation Coefficients Linear Regression Procedure Assumptions Linear Regression Formulas Sample Problem Chapter Summary Chapter Review Exercises 8 Nonparametric Statistics Underlying Assumptions Concerning Nonparametric Statistics Chi-square Test for Goodness of Fit Degrees of Freedom Test Assumptions Hypothesis Construction Test Formula Determining the Critical Value Sample Problem c2 Test of Independence Degrees of Freedom Expected Number of Cases Test Assumptions Hypothesis Construction Test Formula Sample Problem Cochran's Q Test Test Assumptions Hypothesis Construction Cochran's Q Test Formula Sample Problem Cochran's Q Test Test Assumptions Hypothesis Construction Test Formula Sample Problem Chapter Summary Chapter Review Exercises 9 Survey Research Types of Survey Studies Collecting and Maintaining Survey Data Outline for Planning a Survey Constructing the Instrument Types of Survey Items Forms of Questions Unstructured Questions Structured Questions Rating Scales Likert Scales Semantic Differential Scales Formatting Questionnaires for the Mail Sound Survey Research Procedures Measurable Objective Representative Population Match the Hypothesis to the Statistical Tests Conduct Background Research Instrument Validity and Reliability Cover Letters and Instructions Sampling for Surveys Calculating Sample Sizes Survey Research Limitations Pilot Testing Permission to Use Human Subjects Chapter Summary Chapter Review Exercises 10 Experimental Design Experimental Design Uses Research Hypotheses and Experimental Design Dependent and Independent Variables Types of Experimental Designs One-way ANOVA Completely Randomized Design Randomized Block Design Latin Square Design Completely Randomized Factorial Design Chapter Summary Chapter Review Exercises 11 Presenting Research Data Presentation for Safety Professionals Displaying Descriptive Statistics Displaying Tables Column Charts Pie Charts Presenting Inferential Statistics z-Tests and t-Tests Example Results from a Paired t-Test Procedure One-way Analysis of Variance Correlation Procedures Regression Procedures Nonparametric Procedures Using Computer Software to Develop Presentations Sample Data Analysis Using Microsoft Excel Developing Presentations Using Microsoft Office Chapter Summary Chapter Review Exercises Appendix Statistical Tables Cumulative Distribution Function for the Standard Normal Random Variable Critical Values for the t Distribution Critical Values for the Chi-square Distribution Critical Values for the F Distribution Table of Random Units Critical Values of the Studentized Range Glossary References Solutions to Selected Problems Index

Christopher A. Janicak, Ph.D., CSP, ARM, is a Professor of Safety and Graduate Program Coordinator at Indiana University of Pennsylvania, Department of Safety Sciences. Dr. Janicak has over 20 years of professional experience in safety as a loss control consultant, safety manager, and university professor. He has presented at many national and international conferences, and has published books, book chapters, and journal articles in the field of occupational safety.

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