Applied Statistics in Occupational Safety and Health

by Christopher A. Janicak, Majed Zreiqat

Overview

This completely updated fourth edition is designed to provide safety professionals or those studying to become safety professionals with the basic methods and principles necessary to apply statistics properly. Safety professionals often encounter statistics in the literature they read and are required to present findings or make decisions based on data analyses. Statistics can be used to justify the implementation of a program, identify areas that need to be addressed, or justify the impact that various safety programs have on losses and accidents. Safety professionals also use a variety of data in their day-to-day work.

Applied Statistics in Occupational Safety and Health presents the reader with practical information to make their job easier. In addition to sample problems and solutions, the authors include easy-to-read charts and tables, appendices containing statistical tables, and a glossary of terms.

Product Details

ISBN-13:	9781636713793
Publisher:	Bloomsbury Academic
Publication date:	04/07/2023
Edition description:	Fourth Edition
Pages:	226
Product dimensions:	7.00(w) x 10.00(h) x 0.48(d)

About the Author

Christopher A. Janicak, Ph.D., CSP, CEA, CFPS, ARM, is a retired professor of safety sciences from Indiana University of Pennsylvania. He has over 35 years of professional experience in the field. He has a BS degree in Health and Safety Studies from the University of Illinois at Urbana Champaign, an MS degree in Industrial Technology – Industrial Safety Concentration from Illinois State University, and a Ph.D. in Research methods from Loyola University of Chicago. He has taught courses in statistics and research methods at the MS and Ph.D. levels along with occupational safety courses in the areas of industrial fire protection, ergonomics, and systems safety to name a few. He has numerous research studies published in various peer reviewed publications.

Majed Zreiqat, Ph.D. CSP, is an associate professor of Safety Sciences from Indiana University of Pennsylvania (IUP) with nine years of teaching experience in the occupational health and safety field. He received his Doctor of Philosophy degree (Ph.D.) in Occupational Safety and Health from West Virginia University (WVU) with a minor in Applied Statistics in 2014. He has an M.S. in Safety Sciences from Indiana University of Pennsylvania (IUP) in 2008 and a B.S. in Chemical Engineering from the University of Jordan in 1995. He has more than ten years of work experience as a chemical and process safety engineer. He has taught advanced statistics courses and research methods for safety sciences, process and system safety, hazardous material safety, fire safety, etc. His research areas of expertise are in Ergonomics and Human Factors. He has several scholarly activities including peer-reviewed publications and conference presentations.

Table of Contents

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

Editorial Reviews

Provides occupational safety and health professionals with an introductory guide to basic statistic and data analysis. Uses step-by- step methods and examples and applications common to safety professionals to explain how to apply appropriate statistical procedures to commonly encountered situations. Gives methods for applying statistics properly, describes detailed procedures for each statistical test and methods for using them, presents descriptive statistical concepts and explains how they can be used to summarize data, and examines inferential statistics for parametric and non- parametric procedures. Includes summaries, exercises, and solutions, plus five appendices of statistical tables. The author is assistant professor of safety and director of the Safety Program at Illinois State University. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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