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Classic topics on the history of modern mathematical statistics : from Laplace to more recent times / / Prakash Gorroochurn
| Classic topics on the history of modern mathematical statistics : from Laplace to more recent times / / Prakash Gorroochurn |
| Autore | Gorroochurn Prakash <1971-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , [2016] |
| Descrizione fisica | 1 online resource (779 p.) |
| Disciplina | 519.509 |
| Collana | THEi Wiley ebooks |
| Soggetto topico |
Mathematical statistics - History
Probabilities - History |
| ISBN |
1-119-12794-7
1-119-12793-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The Laplacean revolution -- Galton, regression, and correlation -- Karl Pearson's chi-squared goodness-of-fit test -- Student's test -- the Fisherian legacy -- Beyond Fisher and Neyman-Pearson. |
| Record Nr. | UNINA-9910136778403321 |
Gorroochurn Prakash <1971->
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classic topics on the history of modern mathematical statistics : from Laplace to more recent times / / Prakash Gorroochurn
| Classic topics on the history of modern mathematical statistics : from Laplace to more recent times / / Prakash Gorroochurn |
| Autore | Gorroochurn Prakash <1971-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , [2016] |
| Descrizione fisica | 1 online resource (779 p.) |
| Disciplina | 519.509 |
| Collana | THEi Wiley ebooks |
| Soggetto topico |
Mathematical statistics - History
Probabilities - History |
| ISBN |
1-119-12794-7
1-119-12793-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The Laplacean revolution -- Galton, regression, and correlation -- Karl Pearson's chi-squared goodness-of-fit test -- Student's test -- the Fisherian legacy -- Beyond Fisher and Neyman-Pearson. |
| Record Nr. | UNINA-9910814550203321 |
|
Gorroochurn Prakash <1971->
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data analysis [[electronic resource] ] : what can be learned from the past 50 years / / Peter J. Huber
| Data analysis [[electronic resource] ] : what can be learned from the past 50 years / / Peter J. Huber |
| Autore | Huber Peter J |
| Edizione | [First edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , c2011 |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina |
519.5
519.509 |
| Collana | Wiley series in probability and statistics. |
| Soggetto topico |
Mathematical statistics - History
Mathematical statistics - Philosophy Numerical analysis - Methodology |
| ISBN |
1-283-10931-X
9786613109316 1-118-01825-7 1-118-01824-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
DATA ANALYSIS: What Can Be Learned From the Past 50 Years; CONTENTS; Preface; 1 What is Data Analysis?; 1.1 Tukey's 1962 paper; 1.2 The Path of Statistics; 2 Strategy Issues in Data Analysis; 2.1 Strategy in Data Analysis; 2.2 Philosophical issues; 2.2.1 On the theory of data analysis and its teaching; 2.2.2 Science and data analysis; 2.2.3 Economy of forces; 2.3 Issues of size; 2.4 Strategic planning; 2.4.1 Planning the data collection; 2.4.2 Choice of data and methods; 2.4.3 Systematic and random errors; 2.4.4 Strategic reserves; 2.4.5 Human factors; 2.5 The stages of data analysis
2.5.1 Inspection2.5.2 Error checking; 2.5.3 Modification; 2.5.4 Comparison; 2.5.5 Modeling and Model fitting; 2.5.6 Simulation; 2.5.7 What-if analyses; 2.5.8 Interpretation; 2.5.9 Presentation of conclusions; 2.6 Tools required for strategy reasons; 2.6.1 Ad hoc programming; 2.6.2 Graphics; 2.6.3 Record keeping; 2.6.4 Creating and keeping order; 3 Massive Data Sets; 3.1 Introduction; 3.2 Disclosure: Personal experiences; 3.3 What is massive? A classification of size; 3.4 Obstacles to scaling; 3.4.1 Human limitations: visualization; 3.4.2 Human - machine interactions 3.4.3 Storage requirements3.4.4 Computational complexity; 3.4.5 Conclusions; 3.5 On the structure of large data sets; 3.5.1 Types of data; 3.5.2 How do data sets grow?; 3.5.3 On data organization; 3.5.4 Derived data sets; 3.6 Data base management and related issues; 3.6.1 Data archiving; 3.7 The stages of a data analysis; 3.7.1 Planning the data collection; 3.7.2 Actual collection; 3.7.3 Data access; 3.7.4 Initial data checking; 3.7.5 Data analysis proper; 3.7.6 The final product: presentation of arguments and conclusions; 3.8 Examples and some thoughts on strategy; 3.9 Volume reduction 3.10 Supercomputers and software challenges3.10.1 When do we need a Concorde?; 3.10.2 General Purpose Data Analysis and Supercomputers; 3.10.3 Languages, Programming Environments and Databased Prototyping; 3.11 Summary of conclusions; 4 Languages for Data Analysis; 4.1 Goals and purposes; 4.2 Natural languages and computing languages; 4.2.1 Natural languages; 4.2.2 Batch languages; 4.2.3 Immediate languages; 4.2.4 Language and literature; 4.2.5 Object orientation and related structural issues; 4.2.6 Extremism and compromises, slogans and reality; 4.2.7 Some conclusions; 4.3 Interface issues 4.3.1 The command line interface4.3.2 The menu interface; 4.3.3 The batch interface and programming environments; 4.3.4 Some personal experiences; 4.4 Miscellaneous issues; 4.4.1 On building blocks; 4.4.2 On the scope of names; 4.4.3 On notation; 4.4.4 Book-keeping problems; 4.5 Requirements for a general purpose immediate language; 5 Approximate Models; 5.1 Models; 5.2 Bayesian modeling; 5.3 Mathematical statistics and approximate models; 5.4 Statistical significance and physical relevance; 5.5 Judicious use of a wrong model; 5.6 Composite models; 5.7 Modeling the length of day 5.8 The role of simulation |
| Record Nr. | UNINA-9910139454503321 |
|
Huber Peter J
|
||
| Hoboken, New Jersey : , : Wiley, , c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data analysis : what can be learned from the past 50 years / / Peter J. Huber
| Data analysis : what can be learned from the past 50 years / / Peter J. Huber |
| Autore | Huber Peter J |
| Edizione | [First edition] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2011 |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina |
519.5
519.509 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Mathematical statistics - History
Mathematical statistics - Philosophy Numerical analysis - Methodology |
| ISBN |
9786613109316
9781283109314 128310931X 9781118018255 1118018257 9781118018248 1118018249 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
DATA ANALYSIS: What Can Be Learned From the Past 50 Years; CONTENTS; Preface; 1 What is Data Analysis?; 1.1 Tukey's 1962 paper; 1.2 The Path of Statistics; 2 Strategy Issues in Data Analysis; 2.1 Strategy in Data Analysis; 2.2 Philosophical issues; 2.2.1 On the theory of data analysis and its teaching; 2.2.2 Science and data analysis; 2.2.3 Economy of forces; 2.3 Issues of size; 2.4 Strategic planning; 2.4.1 Planning the data collection; 2.4.2 Choice of data and methods; 2.4.3 Systematic and random errors; 2.4.4 Strategic reserves; 2.4.5 Human factors; 2.5 The stages of data analysis
2.5.1 Inspection2.5.2 Error checking; 2.5.3 Modification; 2.5.4 Comparison; 2.5.5 Modeling and Model fitting; 2.5.6 Simulation; 2.5.7 What-if analyses; 2.5.8 Interpretation; 2.5.9 Presentation of conclusions; 2.6 Tools required for strategy reasons; 2.6.1 Ad hoc programming; 2.6.2 Graphics; 2.6.3 Record keeping; 2.6.4 Creating and keeping order; 3 Massive Data Sets; 3.1 Introduction; 3.2 Disclosure: Personal experiences; 3.3 What is massive? A classification of size; 3.4 Obstacles to scaling; 3.4.1 Human limitations: visualization; 3.4.2 Human - machine interactions 3.4.3 Storage requirements3.4.4 Computational complexity; 3.4.5 Conclusions; 3.5 On the structure of large data sets; 3.5.1 Types of data; 3.5.2 How do data sets grow?; 3.5.3 On data organization; 3.5.4 Derived data sets; 3.6 Data base management and related issues; 3.6.1 Data archiving; 3.7 The stages of a data analysis; 3.7.1 Planning the data collection; 3.7.2 Actual collection; 3.7.3 Data access; 3.7.4 Initial data checking; 3.7.5 Data analysis proper; 3.7.6 The final product: presentation of arguments and conclusions; 3.8 Examples and some thoughts on strategy; 3.9 Volume reduction 3.10 Supercomputers and software challenges3.10.1 When do we need a Concorde?; 3.10.2 General Purpose Data Analysis and Supercomputers; 3.10.3 Languages, Programming Environments and Databased Prototyping; 3.11 Summary of conclusions; 4 Languages for Data Analysis; 4.1 Goals and purposes; 4.2 Natural languages and computing languages; 4.2.1 Natural languages; 4.2.2 Batch languages; 4.2.3 Immediate languages; 4.2.4 Language and literature; 4.2.5 Object orientation and related structural issues; 4.2.6 Extremism and compromises, slogans and reality; 4.2.7 Some conclusions; 4.3 Interface issues 4.3.1 The command line interface4.3.2 The menu interface; 4.3.3 The batch interface and programming environments; 4.3.4 Some personal experiences; 4.4 Miscellaneous issues; 4.4.1 On building blocks; 4.4.2 On the scope of names; 4.4.3 On notation; 4.4.4 Book-keeping problems; 4.5 Requirements for a general purpose immediate language; 5 Approximate Models; 5.1 Models; 5.2 Bayesian modeling; 5.3 Mathematical statistics and approximate models; 5.4 Statistical significance and physical relevance; 5.5 Judicious use of a wrong model; 5.6 Composite models; 5.7 Modeling the length of day 5.8 The role of simulation |
| Record Nr. | UNINA-9910825732703321 |
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Huber Peter J
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| Hoboken, N.J., : Wiley, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A history of parametric statistical inference from Bernoulli to Fisher, 1713-1935 / Anders Hald
| A history of parametric statistical inference from Bernoulli to Fisher, 1713-1935 / Anders Hald |
| Autore | Hald, Anders |
| Pubbl/distr/stampa | New York : Springer, c2007 |
| Descrizione fisica | ix, 223 p. : ill. ; 25 cm |
| Disciplina | 519.54 |
| Collana | Sources and studies in the history of mathematics and physical sciences |
| Soggetto topico | Mathematical statistics - History |
| ISBN | 0387464085 |
| Classificazione |
AMS 01-XX
LC QA276.15.H353 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991003449179707536 |
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Hald, Anders
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| New York : Springer, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Statistical thought : a perspective and history / Shoutir Kishore Chatterjee
| Statistical thought : a perspective and history / Shoutir Kishore Chatterjee |
| Autore | Chatterjee, Shoutir Kishore |
| Pubbl/distr/stampa | Oxford ; New York : Oxford University Press, 2003 |
| Descrizione fisica | xix, 416 p. ; 25 cm |
| Disciplina | 519.509 |
| Soggetto topico | Mathematical statistics - History |
| ISBN | 0198525311 |
| Classificazione |
AMS 62-02
AMS 62-03 LC QA276.15.C43 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Part I: Perspective ; 1. Philosophical background ; 2. Statistical induction-when and how? ; 3. Interpretation of probability: various nuances ; 4. Bearing of interpretations of probability on statistical induction
Part II: History ; 5. Prehistory, beginning of history, and the toddling period ; 6. New concepts and methods--pre-Bayesian era ; 7. Beginning of the pro-subjective approach ; 8. Pro-subjective approach loses as sampling theory gains ground ; 9. Breaking the barrier: out into a broader domain ; 10. Modern era: the superstructure builds up |
| Record Nr. | UNISALENTO-991001303719707536 |
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Chatterjee, Shoutir Kishore
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| Oxford ; New York : Oxford University Press, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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