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Biblioteca

MARC Lista (tabellare)
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Autore Haller Rudolf (Mathematician)
Edizione [2., überarbeitete Auflage]
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2016]
Descrizione fisica 1 online resource (499 p.)
Disciplina 519.2/2
Collana De Gruyter Studium
Soggetto topico Stochastik
Wahrscheinlichkeitsrechnung
MATHEMATICS / Probability & Statistics / General
Soggetto genere / forma Electronic books.
ISBN 3-11-048077-8
3-11-048090-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione ger
Nota di contenuto Frontmatter -- Vorwort zur 1. Auflage -- Vorwort zur 2. Auflage -- Inhaltsverzeichnis -- Von den Anfängen bis zum Ende des Mittelalters -- Beginn der Neuzeit -- 1. Hälfte des 17. Jahrhunderts -- HUYGENS' Tractatus de Ratiociniis in Aleae Ludo von 1657 -- 2. Hälfte des 17. Jahrhunderts -- Beginn des 18. Jahrhunderts -- JAKOB BERNOULLIs Ars Conjectandi von 1713 -- MONTMORTs Essay d'Analyse sur les Jeux de Hazard von 1713 -- NIKOLAUS BERNOULLIs Petersburger Problem von 1713 -- Die Jahre nach 1713 bis 1750 -- 2. Hälfte des 18. Jahrhunderts -- 1. Hälfte des 19. Jahrhunderts -- 2. Hälfte des 19. Jahrhunderts -- Das 20. Jahrhundert -- Nachtrag -- Lebensdaten -- Literatur -- Abbildungsverzeichnis -- Personenregister -- Sachregister
Record Nr. UNINA-9910164964103321
Haller Rudolf (Mathematician)  
Berlin ; ; Boston : , : De Gruyter, , [2016]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Autore Haller Rudolf (Mathematician)
Edizione [2., überarbeitete Auflage]
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2016]
Descrizione fisica 1 online resource (499 p.)
Disciplina 519.2/2
Collana De Gruyter Studium
Soggetto topico Stochastik
Wahrscheinlichkeitsrechnung
MATHEMATICS / Probability & Statistics / General
ISBN 3-11-048077-8
3-11-048090-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione ger
Nota di contenuto Frontmatter -- Vorwort zur 1. Auflage -- Vorwort zur 2. Auflage -- Inhaltsverzeichnis -- Von den Anfängen bis zum Ende des Mittelalters -- Beginn der Neuzeit -- 1. Hälfte des 17. Jahrhunderts -- HUYGENS' Tractatus de Ratiociniis in Aleae Ludo von 1657 -- 2. Hälfte des 17. Jahrhunderts -- Beginn des 18. Jahrhunderts -- JAKOB BERNOULLIs Ars Conjectandi von 1713 -- MONTMORTs Essay d'Analyse sur les Jeux de Hazard von 1713 -- NIKOLAUS BERNOULLIs Petersburger Problem von 1713 -- Die Jahre nach 1713 bis 1750 -- 2. Hälfte des 18. Jahrhunderts -- 1. Hälfte des 19. Jahrhunderts -- 2. Hälfte des 19. Jahrhunderts -- Das 20. Jahrhundert -- Nachtrag -- Lebensdaten -- Literatur -- Abbildungsverzeichnis -- Personenregister -- Sachregister
Record Nr. UNINA-9910792676303321
Haller Rudolf (Mathematician)  
Berlin ; ; Boston : , : De Gruyter, , [2016]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Berühmte Aufgaben der Stochastik : Von den Anfängen bis heute / / Rudolf Haller, Friedrich Barth
Autore Haller Rudolf (Mathematician)
Edizione [2., überarbeitete Auflage]
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2016]
Descrizione fisica 1 online resource (499 p.)
Disciplina 519.2/2
Collana De Gruyter Studium
Soggetto topico Stochastik
Wahrscheinlichkeitsrechnung
MATHEMATICS / Probability & Statistics / General
ISBN 3-11-048077-8
3-11-048090-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione ger
Nota di contenuto Frontmatter -- Vorwort zur 1. Auflage -- Vorwort zur 2. Auflage -- Inhaltsverzeichnis -- Von den Anfängen bis zum Ende des Mittelalters -- Beginn der Neuzeit -- 1. Hälfte des 17. Jahrhunderts -- HUYGENS' Tractatus de Ratiociniis in Aleae Ludo von 1657 -- 2. Hälfte des 17. Jahrhunderts -- Beginn des 18. Jahrhunderts -- JAKOB BERNOULLIs Ars Conjectandi von 1713 -- MONTMORTs Essay d'Analyse sur les Jeux de Hazard von 1713 -- NIKOLAUS BERNOULLIs Petersburger Problem von 1713 -- Die Jahre nach 1713 bis 1750 -- 2. Hälfte des 18. Jahrhunderts -- 1. Hälfte des 19. Jahrhunderts -- 2. Hälfte des 19. Jahrhunderts -- Das 20. Jahrhundert -- Nachtrag -- Lebensdaten -- Literatur -- Abbildungsverzeichnis -- Personenregister -- Sachregister
Record Nr. UNINA-9910827623403321
Haller Rudolf (Mathematician)  
Berlin ; ; Boston : , : De Gruyter, , [2016]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Methods and applications of linear models : regression and the analysis of variance / / Ronald R. Hocking, PenHock Statistical Consultants
Methods and applications of linear models : regression and the analysis of variance / / Ronald R. Hocking, PenHock Statistical Consultants
Autore Hocking R. R (Ronald R.), <1932->
Edizione [3rd ed.]
Pubbl/distr/stampa Hoboken, New Jersey : , : John Wiley & Sons, , 2013
Descrizione fisica 1 online resource (717 p.)
Disciplina 519.5/36
Collana Wiley Series in Probability and Statistics
Soggetto topico Regression analysis
Analysis of variance
Linear models (Statistics)
MATHEMATICS / Probability & Statistics / General
Soggetto genere / forma Electronic books.
ISBN 1-118-59302-2
1-118-64019-5
1-118-59304-9
Classificazione MAT029000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Methods and Applications of Linear Models; Contents; Preface to the Third Edition; Preface to the Second Edition; Preface to the First Edition; PART I REGRESSION; 1 Introduction to Linear Models; 1.1 Background Information; 1.2 Mathematical and Statistical Models; 1.3 Definition of the Linear Model; 1.4 Examples of Regression Models; 1.4.1 Single-Variable, Regression Model; 1.4.2 Regression Models with Several Inputs; 1.4.3 Discrete Response Variables; 1.4.4 Multivariate Linear Models; 1.5 Concluding Comments; Exercises; 2 Regression on Functions of One Variable
2.1 The Simple Linear Regression Model2.2 Parameter Estimation; 2.2.1 Least Squares Estimation; 2.2.2 Maximum Likelihood Estimation; 2.2.3 Coded Data: Centering and Scaling; 2.2.4 The Analysis of Variance Table; 2.3 Properties of the Estimators and Test Statistics; 2.3.1 Moments of Linear Functions of Random Variables; 2.3.2 Moments of Least Squares Estimators; 2.3.3 Distribution of the Least Squares Estimators; 2.3.4 The Distribution of Test Statistics; 2.4 The Analysis of Simple Linear Regression Models; 2.4.1 Two Numerical Examples; 2.4.2 A Test for Lack-of-Fit
2.4.3 Inference on the Parameters of the Model2.4.4 Prediction and Prediction Intervals; 2.5 Examining the Data and the Model; 2.5.1 Residuals; 2.5.2 Outliers, Extreme Points, and Influence; 2.5.3 Normality, Independence, and Variance Homogeneity; 2.6 Polynomial Regression Models; 2.6.1 The Quadratic Model; 2.6.2 Higher Ordered Polynomial Models; 2.6.3 Orthogonal Polynomials; 2.6.4 Regression through the Origin; Exercises; 3 Transforming the Data; 3.1 The Need for Transformations; 3.2 Weighted Least Squares; 3.3 Variance Stabilizing Transformations
3.4 Transformations to Achieve a Linear Model3.4.1 Transforming the Dependent Variable; 3.4.2 Transforming the Predictors; 3.5 Analysis of the Transformed Model; 3.5.1 Transformations with Forbes Data; Exercises; 4 Regression on Functions of Several Variables; 4.1 The Multiple Linear Regression Model; 4.2 Preliminary Data Analysis; 4.3 Analysis of the Multiple Linear Regression Model; 4.3.1 Fitting the Model in Centered Form; 4.3.2 Estimation and Analysis of the Original Data; 4.3.3 Model Assessment and Residual Analysis; 4.3.4 Prediction; 4.3.5 Transforming the Response
4.4 Partial Correlation and Added-Variable Plots4.4.1 Partial Correlation; 4.4.2 Added-Variable Plots; 4.4.3 Simple Versus Partial Correlation; 4.5 Variable Selection; 4.5.1 The Case of Orthogonal Predictors; 4.5.2 Criteria for Deletion of Variables; 4.5.3 Nonorthogonal Predictors; 4.5.4 Computational Considerations; 4.5.5 Selection Strategies; 4.6 Model Specification; 4.6.1 Application to Subset Selection; 4.6.2 Improved Mean Squared Error; 4.6.3 Development of the Cp Statistic; Exercises; 5 Collinearity in Multiple Linear Regression; 5.1 The Collinearity Problem; 5.1.1 Introduction
5.1.2 A Simple Example
Record Nr. UNINA-9910452282203321
Hocking R. R (Ronald R.), <1932->  
Hoboken, New Jersey : , : John Wiley & Sons, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and Statistics : A Course for Physicists and Engineers / / Arak M. Mathai, Hans J. Haubold
Probability and Statistics : A Course for Physicists and Engineers / / Arak M. Mathai, Hans J. Haubold
Autore Mathai Arak M.
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2017]
Descrizione fisica 1 online resource (604 p.)
Disciplina 519.2
Collana De Gruyter Textbook
Soggetto topico Engineering - Statistical methods
Probabilities
Modellbildung
Statistik
Versuchsplanung
Wahrscheinlichkeitsrechnung
Wahrscheinlichkeitstheorie
MATHEMATICS / Probability & Statistics / General
Soggetto genere / forma Electronic books.
Classificazione SK 800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Introduction / Mathai, A. M. / Haubold, Hans J. -- Preface / Mathai, A. M. / Haubold, Hans J. -- Acknowledgement -- Contents -- List of Tables -- List of Symbols -- 1. Random phenomena -- 2. Probability -- 3. Random variables -- 4. Expected values -- 5. Commonly used discrete distributions -- 6. Commonly used density functions -- 7. Joint distributions -- 8. Some multivariate distributions -- 9. Collection of random variables -- 10. Sampling distributions -- 11. Estimation -- 12. Interval estimation -- 13. Tests of statistical hypotheses -- 14. Model building and regression -- 15. Design of experiments and analysis of variance -- 16. Questions and answers -- Tables of percentage points -- References -- Index
Record Nr. UNINA-9910258747703321
Mathai Arak M.  
Berlin ; ; Boston : , : De Gruyter, , [2017]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Probability and Statistics : A Course for Physicists and Engineers / / Arak M. Mathai, Hans J. Haubold
Probability and Statistics : A Course for Physicists and Engineers / / Arak M. Mathai, Hans J. Haubold
Autore Mathai Arak M.
Pubbl/distr/stampa Berlin ; ; Boston : , : De Gruyter, , [2017]
Descrizione fisica 1 online resource (604 p.)
Disciplina 519.2
Collana De Gruyter Textbook
Soggetto topico Engineering - Statistical methods
Probabilities
Modellbildung
Statistik
Versuchsplanung
Wahrscheinlichkeitsrechnung
Wahrscheinlichkeitstheorie
MATHEMATICS / Probability & Statistics / General
Classificazione SK 800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Introduction / Mathai, A. M. / Haubold, Hans J. -- Preface / Mathai, A. M. / Haubold, Hans J. -- Acknowledgement -- Contents -- List of Tables -- List of Symbols -- 1. Random phenomena -- 2. Probability -- 3. Random variables -- 4. Expected values -- 5. Commonly used discrete distributions -- 6. Commonly used density functions -- 7. Joint distributions -- 8. Some multivariate distributions -- 9. Collection of random variables -- 10. Sampling distributions -- 11. Estimation -- 12. Interval estimation -- 13. Tests of statistical hypotheses -- 14. Model building and regression -- 15. Design of experiments and analysis of variance -- 16. Questions and answers -- Tables of percentage points -- References -- Index
Record Nr. UNISA-996309060403316
Mathai Arak M.  
Berlin ; ; Boston : , : De Gruyter, , [2017]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Statistics for business / / Perumal Mariappan
Statistics for business / / Perumal Mariappan
Autore Mariappan Perumal
Pubbl/distr/stampa Boca Raton, FL : , : CRC Press, , 2019
Descrizione fisica 1 online resource
Disciplina 519.5
Soggetto topico Commercial statistics
MATHEMATICS / Applied
MATHEMATICS / Probability & Statistics / General
BUSINESS & ECONOMICS / Management Science
REFERENCE / General
ISBN 0-429-81150-0
0-429-44324-2
0-429-81149-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910793515703321
Mariappan Perumal  
Boca Raton, FL : , : CRC Press, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Statistics for business / / Perumal Mariappan
Statistics for business / / Perumal Mariappan
Autore Mariappan Perumal
Edizione [1st ed.]
Pubbl/distr/stampa Boca Raton, FL : , : CRC Press, , 2019
Descrizione fisica 1 online resource
Disciplina 519.5
Soggetto topico Commercial statistics
MATHEMATICS / Applied
MATHEMATICS / Probability & Statistics / General
BUSINESS & ECONOMICS / Management Science
REFERENCE / General
ISBN 0-429-81150-0
0-429-44324-2
0-429-81149-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 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.
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.
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 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.
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).
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.
Record Nr. UNINA-9910955812503321
Mariappan Perumal  
Boca Raton, FL : , : CRC Press, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Statistics Using Python
Statistics Using Python
Autore Campesato Oswald
Edizione [1st ed.]
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2023
Descrizione fisica 1 online resource (273 pages)
Soggetto topico Python (Computer program language) - Statistical methods
MATHEMATICS / Probability & Statistics / General
ISBN 9781683928782
1683928784
9781683928799
1683928792
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front Cover -- Half-Title Page -- LICENSE, DISCLAIMER OF LIABILITY, AND LIMITED WARRANTY -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- CHAPTER 1: Working with Data -- What is Data Literacy? -- Exploratory Data Analysis (EDA) -- Dealing with Data: What Can Go Wrong? -- An Explanation of Data Types -- Working with Data Types -- What is Drift? -- Discrete Data Versus Continuous Data -- Binning Data Values -- Correlation -- Working with Synthetic Data -- Summary -- CHAPTER 2: Introduction to Probability -- What is Set Theory? -- Open, Closed, Compact, and Convex Sets (Optional) -- Concepts in Probability -- Set Theory and Probability -- Coin Tossing Probabilities -- Dice Tossing Probabilities -- Card Drawing Probabilities -- Container-Based Probabilities -- Children-Related Probabilities -- Summary -- CHAPTER 3: Introduction to Statistics -- Introduction to Statistics -- Basic Concepts in Statistics -- The Variance and Standard Deviation -- The Moments of a Function (Optional) -- Random Variables -- Multiple Random Variables -- Sampling Techniques for a Population -- What is Bias? -- Two Important Results in Probability -- Summary -- CHAPTER 4: Metrics in Statistics -- The Confusion Matrix -- The ROC Curve and AUC Curve -- The sklearn.metrics Module (Optional) -- Statistical Metrics for Categorical Data -- Metrics for Continuous Data -- MAE, MSE, and RMSE -- Approximating Linear Data with np.linspace() -- Summary -- CHAPTER 5: Probability Distributions -- PDF, CDF, and PMF -- Two Types of Probability Distributions -- Discrete Probability Distributions -- Continuous Probability Distributions -- Advanced Probability Functions -- Non-Gaussian Distributions -- The Best-Fitting Distribution for Data -- Summary -- CHAPTER 6: Hypothesis Testing -- What is Hypothesis Testing? -- Components of Hypothesis Testing -- Test Statistics.
Working with p-values -- Working with Alpha Values -- Point Estimation, Confidence Level, and Confidence Intervals -- What is A/B Testing? -- The Lifespan of an A/B Test -- Maximum Likelihood Estimation (MLE) -- Summary -- Appendix A: Introduction to Python -- Tools for Python -- Python Installation -- Setting the PATH Environment Variable (Windows Only) -- Launching Python on Your Machine -- Identifiers -- Lines, Indentation, and Multi-Line Statements -- Quotation Marks and Comments -- Saving Your Code in a Module -- Some Standard Modules -- The help() and dir() Functions -- Compile Time and Runtime Code Checking -- Simple Data Types -- Working with Numbers -- Working with Fractions -- Unicode and UTF-8 -- Working with Strings -- Slicing and Splicing Strings -- Search and Replace a String in Other Strings -- Remove Leading and Trailing Characters -- Printing Text without New Line Characters -- Text Alignment -- Working with Dates -- Exception Handling -- Handling User Input -- Python and Emojis (Optional) -- Command-Line Arguments -- Summary -- Appendix B: Introduction to Pandas -- What is Pandas? -- A Pandas Data Frame with a NumPy Example -- Describing a Pandas Data Frame -- Boolean Data Frames -- Data Frames and Random Numbers -- Reading CSV Files in Pandas -- The loc() and iloc() Methods -- Converting Categorical Data to Numeric Data -- Matching and Splitting Strings -- Converting Strings to Dates -- Working with Date Ranges -- Detecting Missing Dates -- Interpolating Missing Dates -- Other Operations with Dates -- Merging and Splitting Columns in Pandas -- Reading HTML Web Pages -- Saving a Pandas Data Frame as an HTML Web Page -- Summary -- Index.
Record Nr. UNINA-9911007182203321
Campesato Oswald  
Bloomfield : , : Mercury Learning & Information, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui