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[null,"1.","Record Nr.",null,"UNINA9910962231803321"]
[null,null,"Titolo",null,"Teaching epidemiology / / edited by Jrn Olsen, Rodolfo Saracci, Dimitrios Trichopoulos"]
[null,null,"Pubbl/distr/stampa",null,"Oxford ; ; New York, : Oxford University Press, 2010"]
[null,null,"ISBN",null,"0-19-157539-9"]
[null,null,"Edizione",null,"[3rd ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (566 pages)"]
[null,null,"Disciplina",null,"614.40711"]
[null,null,"Soggetti",null,"Epidemiology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"pt. 1. Context -- pt. 2. Exposure-oriented epidemiology -- pt. 3. Outcome-oriented epidemiology -- pt. 4. Pedagogies."]
[null,null,null,"Sommario/riassunto","Teaching epidemiology requires skill and knowledge, combined with a clear teaching strategy and good pedagogic skills. The general advice is simple: if you are not an expert on a topic, try to enrich your background knowledge before you start teaching. Teaching Epidemiology, third edition helps you to do this, and by providing the world-expert teacher's advice on how best to structure teaching gives a unique insight in to what has worked in their hands. The book will help you plan your own tailored teaching program.  The book is a guide to new teachers in the field at two levels; those teaching basic courses for undergraduates, and those teaching more advanced courses for students at postgraduate level. Each chapter provides key concepts and a list of key references. Subject specific methodology and disease specific issues (from cancer to genetic epidemiology) are dealt with in details. There is also a focused chapter on the principles and practice of computer-assisted learning."]
[null,"2.","Record Nr.",null,"UNINA9910955812503321"]
[null,null,"Autore",null,"Mariappan Perumal"]
[null,null,"Titolo",null,"Statistics for business / / Perumal Mariappan"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, FL : , : CRC Press, , 2019"]
[null,null,"ISBN",null,"0-429-81150-0"]
[{"$nulls":4},"0-429-44324-2"]
[{"$nulls":4},"0-429-81149-7"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Disciplina",null,"519.5"]
[null,null,"Soggetti",null,"Commercial statistics"]
[{"$nulls":4},"MATHEMATICS / Applied"]
[{"$nulls":4},"MATHEMATICS / Probability & Statistics / General"]
[{"$nulls":4},"BUSINESS & ECONOMICS / Management Science"]
[{"$nulls":4},"REFERENCE / General"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Foreword -- Preface -- Acknowledgements -- Author -- 1: Introduction to Statistics and Its Business Applications -- 1.1 Introduction -- 1.2 Is Statistics a Science? -- 1.3 Application of Statistics in Business -- 1.3.1 The Phases of the Statistical Decision-Making Process -- 1.3.1.1 Study Design Phase -- 1.3.1.2 Data Collection -- 1.3.1.3 Data Analysis -- 1.3.1.4 Action on Results -- 1.4 Responsibility of the Decision Maker -- 1.5 Functions and Limitations of Statistics -- 1.5.1 Functions of Statistics -- 1.5.2 Limitations of Statistics -- 1.6 Distrust of Statistics -- 1.7 Nature of Statistical Law -- 1.7.1 Law of Statistical Regularity -- 1.7.2 Law of Inertia of Large Numbers -- Exercise 1 -- 2: Data Structures, Data Sources, and Data Collection -- 2.1 Introduction -- 2.2 Data Structures -- 2.2.1 Univariate Data -- 2.2.2 Bivariate Data -- 2.2.3 Multivariate Data -- 2.3 Data Sources -- 2.3.1 Primary Sources -- 2.3.2 Secondary Sources -- 2.3.3 Internal Source -- 2.3.4 External Source -- 2.4 Data Collection Inquiries -- 2.4.1 Survey Design -- 2.4.1.1 Questionnaire Design -- 2.4.2 Pilot Survey of the Questionnaire -- 2.4.3 Editing Primary Data -- 2.4.4 Possible Errors in Secondary Data -- 2.4.5 Census and Sampling Methods -- Exercise 2 -- 3: Data Presentation -- 3.1 Introduction -- 3.2 Classification of Data -- 3.2.1 Types of Classification -- 3.3 Data "]
[{"$nulls":4},"Presentation -- 3.3.1 Textual Form -- 3.3.2 Tabular Form -- 3.4 Types of Variables and Data -- 3.5 Levels of Measurement -- 3.5.1 Nominal Scale -- 3.5.2 Ordinal Scale -- 3.5.3 Interval Scale -- 3.5.4 Ratio Scale -- 3.6 Frequency -- 3.6.1 Frequency Distributions -- 3.7 Types of Class Interval -- 3.8 Tally Mark -- 3.9 Construction of a Discrete Frequency Distribution."]
[{"$nulls":4},"3.10 Construction of a Continuous Frequency Distribution -- 3.11 Cumulative and Relative Frequencies -- 3.12 Diagrammatic Representation of Data -- 3.12.1 Advantages and Disadvantages of Diagrammatic Representation -- 3.12.2 Types of Diagrams -- 3.12.2.1 Bar Diagram -- 3.12.2.2 Pie Diagram -- 3.12.2.3 Histogram, Frequency Polygon, and Frequency Curve -- 3.12.2.4 Frequency Polygon -- 3.12.2.5 Frequency Curve -- 3.12.2.6 Ogive Curve -- 3.12.2.7 Line Diagram -- Exercise 3 -- 4: Measures of Central Tendency (MCT) -- 4.1 Introduction -- 4.2 MCT -- 4.2.1 Properties of Best Average -- 4.3 Arithmetic Mean -- 4.3.1 Discrete Data -- 4.3.2 Discrete Data with Frequency -- 4.3.3 Continuous Data with Frequency -- 4.4 Mathematical Properties of Arithmetic Mean -- 4.5 Median -- 4.5.1 Discrete Data -- 4.5.2 Discrete Data with Frequency -- 4.5.3 Continuous Data with Frequency -- 4.5.3.1 Relative Advantages -- 4.5.3.2 Relative Disadvantages -- 4.5.3.3 Property of Median -- 4.5.4 Graphical Method to Find the Median -- 4.6 Quartiles, Deciles and Percentiles -- 4.7 Mode -- 4.7.1 Discrete Data -- 4.7.2 Discrete Data with Frequency -- 4.7.3 Continuous Data with Frequency -- 4.7.4 A Graphical Method to Evaluate the Mode -- 4.8 Comparison of Mean, Median, and Mode -- 4.9 Weighted Arithmetic Mean -- 4.9.1 Advantages of the Weighted Mean -- 4.10 Geometric Mean -- 4.11 Harmonic Mean -- Exercise 4 -- 5: Dispersion -- 5.1 Introduction -- 5.2 Range -- 5.3 Quartile Deviation (QD) -- 5.4 Coefficient of Quartile Deviation -- 5.5 Mean Deviation -- 5.6 Standard Deviation (SD) -- 5.7 Relative Measures of Dispersion -- Exercise 5 -- 6: Skewness, Moments, and Kurtosis -- 6.1 Introduction -- 6.2 Dispersion and Skewness -- 6.3 Moments -- 6.4 Kurtosis -- Exercise 6 -- 7: Correlation and Regression Analysis -- 7.1 Introduction -- 7.2 Correlation -- 7.2.1 Simple Correlation or Correlation."]
[{"$nulls":4},"7.2.2 Rank Correlation -- 7.2.3 Group Correlation -- 7.2.4 Assumptions for Karl Pearson's Coefficient of Correlation -- 7.2.5 Limitations -- 7.2.6 Properties -- 7.2.7 Scatter Diagram -- 7.3 Karl Pearson Coefficient of Correlation -- 7.4 Coefficient of Correlation of a Grouped Data -- 7.5 Probable Error of the Coefficient of Correlation -- 7.6 Rank Correlation -- 7.7 Regression Equations -- Exercise 7 -- 8: Probability -- 8.1 Introduction -- 8.2 Definitions for Certain Key Terms -- 8.2.1 Experiment -- 8.2.2 Sample Space -- 8.2.3 Event -- 8.2.4 Equally Likely Events -- 8.2.5 Mutually Exclusive Events -- 8.2.6 Outcome -- 8.3 Meaning of Probability -- 8.3.1 The Classical Approach -- 8.3.2 The Relative Frequency Approach -- 8.3.3 Notation -- 8.3.4 Addition Rules for Probability -- 8.3.5 Multiplication Rule on Probability When Events Are Independent -- 8.3.6 Compound Probability or Conditional Probability -- 8.4 Bayes' Theorem -- Exercise 8 -- 9: Random Variables and Expectation -- 9.1 Introduction -- 9.2 Random Variable -- 9.2.1 Discrete Random Variable -- 9.2.2 Continuous Random Variable -- 9.3 Probability Distribution -- 9.3.1 Discrete Probability Distribution -- 9.3.2 Characteristics of a Discrete Distribution -- 9.3.3 Probability Function -- 9.4 Mathematical Expectation -- Exercise 9 -- 10: Discrete Probability Distribution: Binomial and Poisson Distributions -- 10.1 Introduction -- 10.2 Binomial Distribution -- 10.2.1 Characteristics of a Bernoulli Process -- 10.2.2 Definition of Binomial Distribution -- 10.2.3 Conditions of "]
[{"$nulls":4},"Binomial Distribution -- 10.2.4 Properties of Binomial Distributions -- 10.2.5 Mean of Binomial Distribution -- 10.2.6 Variance of Binomial Distribution -- 10.3 Poisson Distribution -- 10.3.1 Definition of Poisson Distribution -- 10.3.2 Properties of Poisson Distribution -- 10.3.3 Mean of the Poisson Distribution."]
[{"$nulls":4},"10.3.4 Variance of the Poisson Distribution -- Exercise 10 -- 11: Continuous Probability Distribution: Normal Distribution -- 11.1 Introduction -- 11.2 Definition of Normal Distribution -- 11.3 Standard Normal Distribution -- 11.4 Properties of Normal Distribution -- Exercise 11 -- 12: Theory of Sampling -- 12.1 Introduction -- 12.2 Why Sample? -- 12.3 How to Choose It? -- 12.4 Sample Design -- 12.5 Keywords and Notations -- 12.6 Advantages and Disadvantages of Sampling -- 12.7 Nonrandom Errors and Non-sampling Errors -- 12.8 Random Errors and Sampling Errors -- 12.9 Types of Samples -- 12.9.1 Probability Sample -- 12.9.2 Nonprobability Sample -- 12.10 Random Sampling -- 12.10.1 Systematic Sampling -- 12.10.2 Stratified Sampling (P, N) -- 12.10.3 Multistage Sampling -- 12.11 Nonrandom Sampling Methods -- 12.11.1 Convenience Sampling -- 12.11.2 Purposive Sampling -- 12.11.3 Quota Sampling -- 12.11.4 Cluster Sampling -- 12.11.5 Sequential Sampling -- 12.12 Sampling Distributions -- 12.13 Need for Sampling Distribution -- 12.14 Standard Error for Different Situations -- 12.14.1 When the Population Size Is Infinite -- 12.14.2 When the Population Is Finite -- 12.14.3 Sampling Distribution Based on Sample Means -- 12.15 Point and Internal Estimation -- 12.15.1 Point Estimate -- 12.15.2 Properties of Good Point Estimators -- 12.16 Interval Estimate -- 12.17 Confidence Interval Estimation for Large Samples -- 12.18 Confidence Intervals for Difference between Means -- 12.19 Estimating a Population Proportion -- 12.20 Estimating the Interval Based on the Difference between Two Proportions -- 12.21 Confidence Interval Estimation for Small Sample -- 12.22 Determining the Sample Size -- Exercise 12 -- 13: Hypothesis Testing, Parametric Tests, Distribution Tests, and Tests of Significance -- 13.1 Introduction -- 13.2 Null Hypothesis (H0)."]
[{"$nulls":4},"13.3 Alternative Hypothesis (H1) -- 13.4 Type I and Type II Errors -- 13.5 Meaning of Parametric and Nonparametric Test -- 13.5.1 Parametric Test -- 13.5.2 Nonparametric Test -- 13.6 Selection of Appropriate Test Statistic -- 13.7 Methodology of Statistical Testing -- 13.8 Test for a Specified Mean: Large Sample -- 13.9 Test for Equality of Two Populations: Large Sample -- 13.10 Test for Population Proportion: Large Sample -- 13.11 Test for Equality of Two Proportions: Large Samples -- 13.12 Test for Equality of Two Standard Deviations: Large Samples -- 13.13 Student's t-Distribution -- 13.14 Properties of t-Distribution -- 13.15 Test for the Specified Mean: Small Sample -- 13.16 Test for Equality of Two Population Means: Small Samples -- 13.17 Paired t-Test for Difference of Mean -- 13.18 Chi-square Distribution -- 13.18.1 Properties of Chi-square Distribution -- 13.18.2 Chi-square Test -- 13.18.3 Test for Goodness of Fit -- 13.18.4 Tests for Independence of Attributes -- 13.18.5 Whenever the Expected Frequencies of the Cell Entries Are Less Than 5 -- 13.18.6 Test for a Specified Population Variance -- 13.19 Snedecor's F-Distribution -- 13.19.1 Properties of F-Distribution -- 13.19.2 Test for Difference of Two Populations' Variances -- 13.20 Analysis of Variance (ANOVA) -- 13.20.1 One-Way Classification -- 13.20.2 Two-Way Classification -- Exercise 13 -- Appendix A: Answers to Exercise Problems -- Exercise 4 -- Exercise 5 -- Exercise 6 -- Exercise 7 -- Exercise 8 -- Exercise 9 -- Exercise 10 -- Exercise 11 -- Exercise 12 -- Exercise 13 -- Appendix B: ST Statistical Tables -- Index."]
[null,null,null,"Sommario/riassunto","Statistics for Business is meant as a textbook for students in business, "]
[{"$nulls":4},"computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical model building, and determining the manual solution methods. Special Features: This text is prepared based on \"self-taught\" method. For most of the methods, the required algorithm is clearly explained using flow-charting methodology. More than 200 solved problems provided. More than 175 end-of-chapter exercises with answers are provided. This allows teachers ample flexibility in adopting the textbook to their individual class plans. This textbook is meant to for beginners and advanced learners as a text in Statistics for Business or Applied Statistics for undergraduate and graduate students."]