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E-raamat: Health, Safety, and Environmental Data Analysis: A Business Approach

  • Formaat: 160 pages
  • Ilmumisaeg: 09-Jul-2020
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9780429605451
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Health, Safety, and Environmental Data Analysis: A Business ApproachSuurem pilt
  • Formaat: 160 pages
  • Ilmumisaeg: 09-Jul-2020
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9780429605451
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Provides the quantitative tools and techniques necessary to make important EHS assessments. Coverage includes knowledge of the basic statistical concepts such as presentation of data, measurements of location and dispersion, and elementary probability and distributions; data gathering and analysis topics including sampling methods, sampling theory, testing, and interference as well as skills for critically evaluating published numerical material; and information generation topics. Six examples of projects are included in the final chapter. Annotation c. by Book News, Inc., Portland, Or.

Professionals in environmental health and safety (EHS) management use statistics every day in making decisions. This book was created to provide the quantitative tools and techniques necessary to make important EHS assessments. Readers need not be statistically or mathematically inclined to make the most of this book-mathematical derivations are kept to a minimum and subjects are approached in a simple and factual manner, complemented with plenty of real-world examples.
Chapters 1-3 cover knowledge of basic statistical concepts such as presentation of data, measurements of location and dispersion, and elementary probability and distributions. Data gathering and analysis topics including sampling methods, sampling theory, testing, and interference as well as skills for critically evaluating published numerical material is presented in Chapters 4-6. Chapters 7-11 discuss information generation topics-regression and correlation analysis, time series, linear programming, network and Gnatt charting, and decision analysis-tools that can be used to convert data into meaningful information. Chapter 12 features six examples of projects made successful through statistical approaches being applied. Readers can use these approaches to solve their own unique problems.
Whether you are a EHS professional, manager, or student, Health, Safety, and Environmental Data Analysis: A Business Approach will help you communicate statistical data effectively.

Arvustused

"...succeeds in presenting analytical materials in a most effective narrative style...this text offers a quick, easy reference to assist in converting the collection of required health and safety data into useful, effective tools." -Professional Safety

Preface vii(4)
Overview xi(7)
List of Figures
xviii
List of Tables
xiv
Section A Basic Statistical Concepts 3(46)
1 Presentation of Data
3(18)
1.1 Introduction
3(1)
1.2 Presentation
3(1)
1.3 Accuracy and Errors
4(1)
1.4 Arrays
5(1)
1.5 Tally Marks
5(1)
1.6 Frequency Distribution
5(3)
1.7 Cumulative Frequency Table
8(1)
1.8 Tabulation of Attributes
9(1)
1.9 Graphical Displays
10(5)
1.10 Graphs
15(1)
1.11 Scatter Diagrams
16(1)
1.12 Time Value in Presentation of Data
16(2)
1.13 Key Points in Data Presentation
18(3)
2 Measures of Location and Dispersion
21(12)
2.1 Introduction
21(1)
2.2 Mean
22(1)
2.3 Median
22(1)
2.4 Mode
22(1)
2.5 Percentile
22(1)
2.6 Selecting an Appropriate Measure of Central Tendency
22(1)
2.7 Measures of Dispersion of Discrete Data
23(1)
2.8 Measures of Dispersion of Grouped Data
24(2)
2.9 Other Measures
26(1)
2.10 Application of Mean and Standard Deviation
27(1)
2.11 Rates
28(2)
2.12 Limitations of Rates
30(1)
2.13 Errors in Measures
30(3)
3 Probability and Probability Distributions
33(16)
3.1 Introduction
33(1)
3.2 Simple Events
33(1)
3.3 Compound Events
34(2)
3.4 Expectations
36(1)
3.5 Probability Distributions
37(3)
3.6 Continuous Probability Distributions
40(1)
3.7 Guidelines in Selecting a Probability Distribution
41(1)
3.8 Examples of the Use of Probability Theory
41(8)
Section B Data Gathering and Analysis 49(40)
4 Sampling Methods
49(16)
4.1 Introduction
49(1)
4.2 Requirements of a Good Sample
49(2)
4.3 Sample Size
51(1)
4.4 Sampling Systems
51(2)
4.5 Sampling Considerations
53(2)
4.6 Developing a Questionnaire
55(1)
4.7 Execution of a Survey
55(3)
4.8 Survey Errors
58(1)
4.9 Recommended Attributes of Measurements
58(1)
4.10 Design of Experimental Studies
58(3)
4.11 Quality Control Sampling
61(1)
4.12 Considerations in Statistical Analysis of Occupational Environmental Exposures
61(1)
4.13 Presentation of Report
62(3)
5 Sampling Theory and Estimation
65(6)
5.1 Introduction
65(1)
5.2 Estimates
65(1)
5.3 Point Estimators
66(1)
5.4 Relationship between Mean Point Estimate and Sample Size
67(2)
5.5 Interval Estimates
69(2)
6 Testing and Inference
71(18)
6.1 Introduction
71(1)
6.2 Hypothesis Testing
71(1)
6.3 Hypothesis Tests about a Population Mean: Large Sample
72(1)
6.4 Suggested Steps of Hypothesis Testing
73(1)
6.5 Hypothesis Tests about a Population Mean: Small Sample
74(1)
6.6 Hypothesis Tests about Population Proportion
75(1)
6.7 Hypothesis Tests a Population Variance
76(1)
6.8 Hypothesis Tests of Two Populations: Difference Between Two Means
76(1)
6.9 Hypothesis Tests of Two Populations: Differences Between Two Proportions
77(1)
6.10 Hypothesis Tests of two Populations: Comparing Variances
77(1)
6.11 Hypothesis Tests of more than two Population Means
77(1)
6.12 Hypothesis Testing and Decision Making
77(3)
6.13 Goodness of Fit Test
80(1)
6.14 An Illustrative Example
81(2)
6.15 Non-parametric Methods
83(6)
Section C Information Generation 89(52)
7 Regression and Correlation
89(10)
7.1 Introduction
89(1)
7.2 Regression Equation
89(2)
7.3 Coefficient of Correlation
91(1)
7.4 Testing of Significance
92(1)
7.5 Estimation and Prediction
93(1)
7.6 Residual Analysis
94(1)
7.7 Correlation Analysis
95(1)
7.8 Multiple Regression
95(1)
7.9 An Example
96(3)
8 Time Series
99(8)
8.1 Introduction
99(1)
8.2 Smoothing Method: Moving Average
100(3)
8.3 Forecasting
103(3)
8.4 Exponential Smoothing
106(1)
9 Linear Programming
107(4)
9.1 Introduction
107(1)
9.2 Formulating a Linear Programming Problem
107(1)
9.3 Solving the Problem
108(3)
10 Network and Gnatt Chart
111(8)
10.1 Introduction
111(1)
10.2 Network Analysis Techniques
111(5)
10.3 Allocation of Resources
116(3)
11 Decision Analysis
119(6)
11.1 Introduction
119(1)
11.2 Stages in a Decision-Making Process
120(1)
11.3 Definition of the Problem
120(1)
11.4 Analysis of the System
120(1)
11.5 Constructing the Model
121(1)
11.6 Manipulation and Testing of Model
122(1)
11.7 Implementation
123(1)
11.8 Application of Regression Modeling
123(1)
11.9 Conclusion
124(1)
12 Project Examples
125(16)
12.1 Introduction
125(1)
12.2 Example 1: Decision Tree and Expectation Values
125(4)
12.3 Example 2: Sampling and Estimation
129(1)
12.4 Example 3: Hypothesis Tests with Chi-Squared Distribution
130(4)
12.5 Example 4: Hypothesis tests with t-Distribution
134(2)
12.6 Example 5: Linear Programming
136(2)
12.7 Example 6: Network Analysis
138(3)
Selected Bibliography 141(2)
Index 143
Joseph, Anthony J.
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