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# Applied Statistics In Occupational Safety And Health

## byChristopher A. Janicak

### Paperback | January 9, 2017

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Created for those who have little experience with statistics, or for those who need to keep a concise reference book on hand, this newly updated handbook provides an introductory guide to basic statistics and data analysis.Using step-by-step methods and both examples and applications common to safety professionals, including loss control consultants and occupational health nurses, this new edition makes understanding the "math" side of the job easier. Readers will learn how to apply appropriate statistical procedures to commonly encountered situations, how to perform each statistical test, how to executive inferential statistics for parametric and non-parametric procedures, and how to use descriptive statistical concepts to summarize data.The author ends each chapter with a chapter summary and review exercises. He also includes extensive illustrations, easy-to-read charts and tables, a glossary of statistical terms, a comprehensive index, solutions to sample problems, and five appendices containing statistical tables with their appropriate uses. This third edition provides new examples and numerous updates.

### Details & Specs

Title:Applied Statistics In Occupational Safety And HealthFormat:PaperbackDimensions:188 pages, 9.96 × 6.92 × 0.47 inPublished:January 9, 2017Publisher:Bernan PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1598888889

ISBN - 13:9781598888881

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Table of Contents

ContentsList of Figures and TablesPrefaceAbout the Author1Fundamentals of Statistics Statistics and Their Use in Safety Statistics DefinedCommon Terms and Notations Quantitative and Qualitative Data Statistical NotationsResearch Questions and HypothesesTypes 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 SamplesNonprobability Sample Selection Procedures Chunk Sampling Volunteer Samples Variables Dependent and Independent VariablesChapter SummaryChapter Review Exercises2Probability and Chance Probability Marginal Probabilities Joint Event Probabilities Union Probabilities Conditional ProbabilitiesFactorials, Permutations, Ordered Combinations, and Combinations Factorials Permutations CombinationsBinomial Probabilities Poisson ProbabilityChapter SummaryChapter Review Exercises 3DistributionsStatistical Distributions and PopulationsFrequencies HistogramsFrequency PolygonsPercentages, Cumulative Percentages, and Percentiles Normal Distribution Binomial Distribution t DistributionChi-square Distribution F DistributionChapter SummaryChapter Review Exercises 4Descriptive StatisticsData Formats Categorical Data Ordinal Data Interval Data Ratio Data Strength of the Data Formats Measures of Central Tendency Mean Median ModeMeasures of Variability Range Variance Standard Deviation Interquartile Range z Scores z Scores and Percentages of the PopulationConfidence Intervals for Means 95% Confidence Intervals 99% Confidence Intervals Interpreting Confidence Intervals Chapter SummaryChapter Review Exercises 5Statistical Tests Statistical Hypotheses Inferential Statistical TestingType 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 DecisionChapter Summary Chapter Review Exercises 6Inferential Statistics for Meansz-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 SamplesPaired 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 TestsChapter Summary Chapter Review Exercises 7Correlation and RegressionCorrelation 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 CoefficientsLinear Regression Procedure Assumptions Linear Regression Formulas Sample Problem Chapter Summary Chapter Review Exercises 8Nonparametric StatisticsUnderlying 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 SummaryChapter Review Exercises 9Survey Research Types of Survey StudiesCollecting and Maintaining Survey DataOutline for Planning a SurveyConstructing the InstrumentTypes of Survey Items Forms of Questions Unstructured Questions Structured Questions Rating ScalesLikert 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 10Experimental 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 DesignChapter Summary Chapter Review Exercises 11Presenting Research Data Presentation for Safety Professionals Displaying Descriptive Statistics Displaying Tables Column Charts Pie ChartsPresenting 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 AppendixStatistical 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 GlossaryReferences Solutions to Selected Problems Index