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Excel 2019 for social science statistics : a guide to solving practical problems / / Thomas J. Quirk
| Excel 2019 for social science statistics : a guide to solving practical problems / / Thomas J. Quirk |
| Autore | Quirk Thomas J. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XVII, 246 p. 166 illus., 165 illus. in color.) |
| Disciplina | 001.422 |
| Collana | Excel for statistics |
| Soggetto topico |
Social sciences - Statistical methods - Data processing
Ciències socials Matemàtica estadística Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-64333-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Acknowledgements -- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 2 Random Number Generator -- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 4 One-Group t-Test for the Mean -- 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- 6 Correlation and Simple Linear Regression -- 7 Multiple Correlation and Multiple Regression -- 8 One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index. |
| Record Nr. | UNISA-996466556403316 |
Quirk Thomas J.
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| Cham, Switzerland : , : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Excel 2019 for social science statistics : a guide to solving practical problems / / Thomas J. Quirk
| Excel 2019 for social science statistics : a guide to solving practical problems / / Thomas J. Quirk |
| Autore | Quirk Thomas J. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XVII, 246 p. 166 illus., 165 illus. in color.) |
| Disciplina | 001.422 |
| Collana | Excel for statistics |
| Soggetto topico |
Social sciences - Statistical methods - Data processing
Ciències socials Matemàtica estadística Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-64333-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Acknowledgements -- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 2 Random Number Generator -- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 4 One-Group t-Test for the Mean -- 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- 6 Correlation and Simple Linear Regression -- 7 Multiple Correlation and Multiple Regression -- 8 One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index. |
| Record Nr. | UNINA-9910484325603321 |
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Quirk Thomas J.
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| Cham, Switzerland : , : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Handbook of computational social science . Volume 2 Data science, statistical modelling, and machine learning methods / / edited by Uwe Engel [and three others]
| Handbook of computational social science . Volume 2 Data science, statistical modelling, and machine learning methods / / edited by Uwe Engel [and three others] |
| Pubbl/distr/stampa | Abingdon, Oxon : , : Routledge, , 2022 |
| Descrizione fisica | 1 online resource (435 pages) |
| Disciplina | 519.5028553 |
| Collana | European Association of Methodology Series |
| Soggetto topico |
Social sciences - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN |
1-00-302524-2
1-000-44859-2 1-003-02524-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910772093303321 |
| Abingdon, Oxon : , : Routledge, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Introducing Lisrel [[electronic resource] ] : a guide for the uninitiated / / Adamantios Diamantopoulos, Judy A. Siguaw
| Introducing Lisrel [[electronic resource] ] : a guide for the uninitiated / / Adamantios Diamantopoulos, Judy A. Siguaw |
| Autore | Diamantopoulos A (Adamantios) |
| Pubbl/distr/stampa | London, : SAGE, 2000 |
| Descrizione fisica | 1 online resource (xii, 171p.) : ill |
| Disciplina | 300.15195 |
| Altri autori (Persone) | SiguawJudy A |
| Collana | Introducing statistical methods |
| Soggetto topico | Social sciences - Statistical methods - Data processing |
| ISBN |
1-4462-2659-X
1-84920-935-9 1-306-32333-9 1-4462-7625-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; About the authors; Preface; Acknowledgements; Chapter 1 - What is LISREL all about?; A brief background; Sequential steps in LISREL modeling; Appendix 1A Variance and Covariance; Appendix 1B Implied covariance matrix; Chapter 2 - Model Conceptualization; Appendix 2A Reflective and formative indicators; Chapter 3 - Path Diagram Construction; Appendix 3A Path diagram construction for a LISREL model; Chapter 4 - Model Specification; Appendix 4A Covariance matrix to be analyzed; Appendix 4B Direct entry of covariance matrix into the SIMPLIS input file
Appendix 4C Selected output from SIMPLIS input file for illustrative model; Appendix 4D Parameter matrices of a comprehensive LISREL model; Appendix 4E Illustrative model In matrix form; Chapter 5 - Model Identification; Chapter 6 - Parameter Estimation; Reading the program output: SIMPLIS format; Reading the program output: LISREL format; Appendix 6A Estimation problems; Appendix 6B Path diagram as produced by LISREL 8 program; Appendix 6C Standardized and completely standardized indirect and total effects; Chapter 7 - Assessment of Model Fit; Overall fit assessment Assessment of measurement model; Assessment of structural model; Power assessment; Appendix 7A Different types of discrepancy in evaluating a LISREL model; Chapter 8 - Model Modification; Specification searches; Diagnostics for model modification; Modification of illustrative model: fit improvement; Modification of illustrative model: model simplification; Chapter 9 - Model Cross-Validation; Cross-validating the illustrative model (final version); Cross-validation and model comparison; Equivalent models; Appendix 9A Simplis input file for validation sample; Chapter 10 - An Introduction to Prelis 2; Appendix 10A Thresholds for ordinal variables; References; Index |
| Record Nr. | UNINA-9910791071803321 |
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Diamantopoulos A (Adamantios)
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| London, : SAGE, 2000 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron
| La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron |
| Autore | Caron Pier-Olivier <1990-> |
| Pubbl/distr/stampa | Québec, Québec : , : Presses de l'Université du Québec, , [2018] |
| Descrizione fisica | 1 online resource (xiv, 262 pages) : illustrations |
| Disciplina | 519.53 |
| Collana | Mesure et évaluation |
| Soggetto topico |
Structural equation modeling - Data processing
Social sciences - Statistical methods - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN | 2-7605-4973-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910467226703321 |
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Caron Pier-Olivier <1990->
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| Québec, Québec : , : Presses de l'Université du Québec, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron
| La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron |
| Autore | Caron Pier-Olivier <1990-> |
| Pubbl/distr/stampa | Québec, Québec : , : Presses de l'Université du Québec, , [2018] |
| Descrizione fisica | 1 online resource (xiv, 262 pages) : illustrations |
| Disciplina | 519.53 |
| Collana | Mesure et évaluation |
| Soggetto topico |
Structural equation modeling - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN | 2-7605-4973-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910793947303321 |
|
Caron Pier-Olivier <1990->
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||
| Québec, Québec : , : Presses de l'Université du Québec, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron
| La modélisation par équations structurelles avec Mplus / / Pier-Olivier Caron |
| Autore | Caron Pier-Olivier <1990-> |
| Pubbl/distr/stampa | Québec, Québec : , : Presses de l'Université du Québec, , [2018] |
| Descrizione fisica | 1 online resource (xiv, 262 pages) : illustrations |
| Disciplina | 519.53 |
| Collana | Mesure et évaluation |
| Soggetto topico |
Structural equation modeling - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN | 2-7605-4973-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910825778103321 |
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Caron Pier-Olivier <1990->
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| Québec, Québec : , : Presses de l'Université du Québec, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910143219303321 |
|
Altman Micah
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| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist [[electronic resource] /] / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910830158403321 |
|
Altman Micah
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||
| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Numerical issues in statistical computing for the social scientist / / Micah Altman, Jeff Gill, Michael P. McDonald
| Numerical issues in statistical computing for the social scientist / / Micah Altman, Jeff Gill, Michael P. McDonald |
| Autore | Altman Micah |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (348 p.) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
GillJeff
McDonaldMichael <1967-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Statistics - Data processing
Social sciences - Statistical methods - Data processing |
| ISBN |
1-280-34479-2
9786610344796 0-470-30664-5 0-471-47574-2 0-471-47576-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Numerical Issues in Statistical Computing for the Social Scientist; Contents; Preface; 1 Introduction: Consequences of Numerical Inaccuracy; 1.1 Importance of Understanding Computational Statistics; 1.2 Brief History: Duhem to the Twenty-First Century; 1.3 Motivating Example: Rare Events Counts Models; 1.4 Preview of Findings; 2 Sources of Inaccuracy in Statistical Computation; 2.1 Introduction; 2.1.1 Revealing Example: Computing the Coefficient Standard Deviation; 2.1.2 Some Preliminary Conclusions; 2.2 Fundamental Theoretical Concepts; 2.2.1 Accuracy and Precision
2.2.2 Problems, Algorithms, and Implementations2.3 Accuracy and Correct Inference; 2.3.1 Brief Digression: Why Statistical Inference Is Harder in Practice Than It Appears; 2.4 Sources of Implementation Errors; 2.4.1 Bugs, Errors, and Annoyances; 2.4.2 Computer Arithmetic; 2.5 Algorithmic Limitations; 2.5.1 Randomized Algorithms; 2.5.2 Approximation Algorithms for Statistical Functions; 2.5.3 Heuristic Algorithms for Random Number Generation; 2.5.4 Local Search Algorithms; 2.6 Summary; 3 Evaluating Statistical Software; 3.1 Introduction; 3.1.1 Strategies for Evaluating Accuracy 3.1.2 Conditioning3.2 Benchmarks for Statistical Packages; 3.2.1 NIST Statistical Reference Datasets; 3.2.2 Benchmarking Nonlinear Problems with StRD; 3.2.3 Analyzing StRD Test Results; 3.2.4 Empirical Tests of Pseudo-Random Number Generation; 3.2.5 Tests of Distribution Functions; 3.2.6 Testing the Accuracy of Data Input and Output; 3.3 General Features Supporting Accurate and Reproducible Results; 3.4 Comparison of Some Popular Statistical Packages; 3.5 Reproduction of Research; 3.6 Choosing a Statistical Package; 4 Robust Inference; 4.1 Introduction; 4.2 Some Clarification of Terminology 4.3 Sensitivity Tests4.3.1 Sensitivity to Alternative Implementations and Algorithms; 4.3.2 Perturbation Tests; 4.3.3 Tests of Global Optimality; 4.4 Obtaining More Accurate Results; 4.4.1 High-Precision Mathematical Libraries; 4.4.2 Increasing the Precision of Intermediate Calculations; 4.4.3 Selecting Optimization Methods; 4.5 Inference for Computationally Difficult Problems; 4.5.1 Obtaining Confidence Intervals with Ill-Behaved Functions; 4.5.2 Interpreting Results in the Presence of Multiple Modes; 4.5.3 Inference in the Presence of Instability 5 Numerical Issues in Markov Chain Monte Carlo Estimation5.1 Introduction; 5.2 Background and History; 5.3 Essential Markov Chain Theory; 5.3.1 Measure and Probability Preliminaries; 5.3.2 Markov Chain Properties; 5.3.3 The Final Word (Sort of); 5.4 Mechanics of Common MCMC Algorithms; 5.4.1 Metropolis-Hastings Algorithm; 5.4.2 Hit-and-Run Algorithm; 5.4.3 Gibbs Sampler; 5.5 Role of Random Number Generation; 5.5.1 Periodicity of Generators and MCMC Effects; 5.5.2 Periodicity and Convergence; 5.5.3 Example: The Slice Sampler; 5.5.4 Evaluating WinBUGS; 5.6 Absorbing State Problem 5.7 Regular Monte Carlo Simulation |
| Record Nr. | UNINA-9910876853803321 |
|
Altman Micah
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||
| Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
