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An introduction to statistical learning : with applications in R / Gareth James ... [et al.]
| An introduction to statistical learning : with applications in R / Gareth James ... [et al.] |
| Pubbl/distr/stampa | New York [etc.] : Springer, 2013 |
| Descrizione fisica | XIV, 426 p. : ill. ; 24 cm |
| Disciplina | 519.50285 |
| Altri autori (Persone) | Gareth, Jamesauthor |
| Collana | Springer texts in statistics ; 103 |
| Soggetto topico |
Statistica matematica
Statistica - Apprendimento - Elaboratori |
| ISBN | 9781461471370 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | und |
| Titolo uniforme | |
| Record Nr. | UNISALENTO-991003746859707536 |
| New York [etc.] : Springer, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Introductory statistics with R / Peter Dalgaard
| Introductory statistics with R / Peter Dalgaard |
| Autore | DALGAARD, Peter |
| Pubbl/distr/stampa | New York [etc.] : Springer, [2002] |
| Descrizione fisica | XV, 267 p. ; 24 cm. |
| Disciplina | 519.50285(Statistica matematica. Uso degli elaboratori elettronici) |
| Collana | Statistics and computing. - New York |
| Soggetto topico |
ELABORATORI ELETTRONICI - Linguaggio R
STATISTICA - Programmi per microelaboratori |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-990005504110203316 |
DALGAARD, Peter
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| New York [etc.] : Springer, [2002] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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L' analisi dei dati con SPSS : guida alla programmazione e alla sintassi dei comandi / Giovanni Di Franco
| L' analisi dei dati con SPSS : guida alla programmazione e alla sintassi dei comandi / Giovanni Di Franco |
| Autore | DI FRANCO, Giovanni |
| Pubbl/distr/stampa | Milano : F. Angeli, copyr. 2009 |
| Descrizione fisica | 173 p. : ill. ; 23 cm |
| Disciplina |
300.2855369
519.50285 |
| Collana | La cassetta degli attrezzi. Strumenti per le scienze umane |
| Soggetto topico |
Microelaboratori - Programmi SPSS per Windows
Scienze sociali - Metodi statistici - Programmi per microelaboratori |
| ISBN | 978-88-568-0754-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Record Nr. | UNISA-990003358990203316 |
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DI FRANCO, Giovanni
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| Milano : F. Angeli, copyr. 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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L' impiego della meccanografia in statistica / Ernesto Morra
| L' impiego della meccanografia in statistica / Ernesto Morra |
| Autore | Morra, Ernesto |
| Pubbl/distr/stampa | Torino, : Einaudi, 1957 |
| Descrizione fisica | 116 p. : ill. ; 24 cm |
| Disciplina | 519.50285 |
| Collana | Serie di statistica- Teoria e applicazioni |
| Soggetto non controllato | statistica - maccanografia |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Titolo uniforme | |
| Record Nr. | UNIPARTHENOPE-000036308 |
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Morra, Ernesto
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| Torino, : Einaudi, 1957 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Parthenope | ||
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Metodi statistici per il record linkage / Istat
| Metodi statistici per il record linkage / Istat |
| Autore | Istituto centrale di statistica |
| Pubbl/distr/stampa | Roma : Istat, 2003 |
| Descrizione fisica | 118 p. ; 26 cm |
| Disciplina | 519.50285(Statistica matematica. Uso degli elaboratori elettronici) |
| Collana | Metodi e norme |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Record Nr. | UNISA-990005514010203316 |
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Istituto centrale di statistica
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| Roma : Istat, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Probability, statistics and simulation : with application programs written in R / / Alberto Rotondi, Paolo Pedroni, and Antonio Pievatolo
| Probability, statistics and simulation : with application programs written in R / / Alberto Rotondi, Paolo Pedroni, and Antonio Pievatolo |
| Autore | Rotondi Alberto |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (643 pages) |
| Disciplina | 519.50285 |
| Collana | Unitext |
| Soggetto topico |
Mathematical statistics
R (Computer program language) Estadística matemàtica R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-09429-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- How to Use the Text -- Contents -- About the Authors -- 1 Probability -- 1.1 Chance, Chaos and Determinism -- 1.2 Some Basic Terms -- 1.3 The Concept of Probability -- 1.4 Axiomatic Probability -- 1.5 Repeated Trials -- 1.6 Elements of Combinatorial Analysis -- 1.7 Bayes' Theorem -- 1.8 Learning Algorithms -- 1.9 Problems -- 2 Representation of Random Phenomena -- 2.1 Introduction -- 2.2 Random Variables -- 2.3 Cumulative or Distribution Function -- 2.4 Data Representation -- 2.5 Discrete Random Variables -- 2.6 Binomial Distribution -- 2.7 Continuous Random Variables -- 2.8 Mean, Sum of Squares, Variance, Standard Deviation and Quantiles -- 2.9 Operators -- 2.10 Simple Random Sample -- 2.11 Convergence Criteria -- 2.12 Problems -- 3 Basic Probability Theory -- 3.1 Introduction -- 3.2 Properties of the Binomial Distribution -- 3.3 Poisson Distribution -- 3.4 Normal or Gaussian Density -- 3.5 The Three-Sigma Law and the Standard Gaussian Density -- 3.6 Central Limit Theorem and Universality of the GaussianCurve -- 3.7 Poisson Stochastic Processes -- 3.8 χ2 Density -- 3.9 Uniform Density -- 3.10 Chebyshev's Inequality -- 3.11 How to Use Probability Calculus -- 3.12 Problems -- 4 Multivariate Probability Theory -- 4.1 Introduction -- 4.2 Multivariate Statistical Distributions -- 4.3 Covariance and Correlation -- 4.4 Two-Dimensional Gaussian Distribution -- 4.5 The General Multidimensional Case -- 4.6 Multivariate Probability Regions -- 4.7 Multinomial Distribution -- 4.8 Problems -- 5 Functions of Random Variables -- 5.1 Introduction -- 5.2 Functions of a Random Variable -- 5.3 Functions of Several Random Variables -- 5.4 Mean and Variance Transformation -- 5.5 Means and Variances for n Variables -- 5.6 Problems -- 6 Basic Statistics: Parameter Estimation -- 6.1 Introduction -- 6.2 Confidence Intervals.
6.3 Confidence Intervals with Pivotal Variables -- 6.4 Mention of the Bayesian Approach -- 6.5 Some Notations -- 6.6 Probability Estimation -- 6.7 Probability Estimation from Large Samples -- 6.8 Poissonian Interval Estimation -- 6.9 Mean Estimation from Large Samples -- 6.10 Variance Estimation from Large Samples -- 6.11 Mean and Variance Estimation for Gaussian Samples -- 6.12 How to Use the Estimation Theory -- 6.13 Estimates from a Finite Population -- 6.14 Histogram Analysis -- 6.15 Estimation of the Correlation -- 6.16 Problems -- 7 Basic Statistics: Hypothesis Testing -- 7.1 Testing One Hypothesis -- 7.2 The Gaussian z-Test -- 7.3 Student's t-Test -- 7.4 Chi-Square Test -- 7.5 Compatibility Check Between Sample and Population -- 7.6 Hypothesis Testing with Contingency Tables -- 7.7 Multiple Tests -- 7.8 Snedecor's F-Test -- 7.9 Analysis of Variance (ANOVA) -- 7.10 Two-Way ANOVA -- 7.11 Problems -- 8 Monte Carlo Methods -- 8.1 Introduction -- 8.2 What Is Monte Carlo? -- 8.3 Mathematical Aspects -- 8.4 Generation of Discrete Random Variables -- 8.5 Generation of Continuous Random Variables -- 8.6 Linear Search Method -- 8.7 Rejection Method -- 8.8 Particular Random Generation Methods -- 8.9 Monte Carlo Analysis of Distributions -- 8.10 Evaluation of Confidence Intervals -- 8.11 Simulation of Counting Experiments -- 8.12 Non-parametric Bootstrap -- 8.13 Hypothesis Test with Simulated Data -- 8.14 Problems -- 9 Applications of Monte Carlo Methods -- 9.1 Introduction -- 9.2 Study of Diffusion Phenomena -- 9.3 Simulation of Stochastic Processes -- 9.4 Number of Workers in a Plant: Synchronous Simulation -- 9.5 Number of Workers in a Plant: Asynchronous Simulation -- 9.6 Kolmogorov-Smirnov Test -- 9.7 Metropolis Algorithm -- 9.8 Ising Model -- 9.9 Definite Integral Calculation -- 9.10 Importance Sampling -- 9.11 Stratified Sampling. 9.12 Multidimensional Integrals -- 9.13 Problems -- 10 Statistical Inference and Likelihood -- 10.1 Introduction -- 10.2 Maximum Likelihood (ML) Method -- 10.3 Estimator Properties -- 10.4 Theorems on Estimators -- 10.5 Confidence Intervals -- 10.6 Least Squares Method and Maximum Likelihood -- 10.7 Best Fit of Densities to Data and Histograms -- 10.8 Weighted Mean -- 10.9 Test of Hypotheses -- 10.10 One- or Two-Sample Tests -- 10.11 Most Powerful Tests -- 10.12 Test Functions -- 10.13 Sequential Tests -- 10.14 Problems -- 11 Least Squares -- 11.1 Introduction -- 11.2 No Errors on Predictors -- 11.3 Errors in Predictors -- 11.4 Least Squares Regression Lines: Unweighted Case -- 11.5 Unweighted Linear Least Squares -- 11.6 Weighted Linear Least Squares -- 11.7 Properties of Least Squares Estimates -- 11.8 Model Testing and Search for Functional Forms -- 11.9 Search for Correlations -- 11.10 Fit Strategies -- 11.11 Nonlinear Least Squares -- 11.12 Problems -- 12 Experimental Data Analysis -- 12.1 Introduction -- 12.2 Terminology -- 12.3 Constant and Variable Physical Quantities -- 12.4 Instrumental Sensitivity and Accuracy -- 12.5 Measurement Uncertainty -- 12.6 Treatment of Systematic Effects -- 12.7 Best Fit with Offset Systematic Errors -- 12.8 Best Fit with Scale Systematic Errors -- 12.9 Indirect Measurements and Error Propagation -- 12.10 Measurement Types -- 12.11 M(0, 0, Δ) Measurements -- 12.12 M(0, σ, 0) Measurements -- 12.13 M(0, σ, Δ) Measurements -- 12.14 M(f, 0, 0) Measurements -- 12.15 M(f, σ, 0), M(f, 0, Δ) and M(f, σ, Δ) Measurements -- 12.16 A Case Study: Millikan's Experiments -- 12.17 Some Remarks on the Scientific Method -- 12.18 Problems -- A Table of Symbols -- B R Software -- C Moment-Generating Functions -- D Solutions of Problems -- E Tables -- E.1 Integral of the Gaussian Density. E.2 Quantiles of the Student's Density -- E.3 Integrals of the Reduced χ2 Density -- E.4 Quantile Values of the Non-Reduced χ2 Density -- E.5 Quantiles of the F Density -- Bibliography -- Index. |
| Record Nr. | UNISA-996503552003316 |
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Rotondi Alberto
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Probability, statistics and simulation : with application programs written in R / / Alberto Rotondi, Paolo Pedroni, and Antonio Pievatolo
| Probability, statistics and simulation : with application programs written in R / / Alberto Rotondi, Paolo Pedroni, and Antonio Pievatolo |
| Autore | Rotondi Alberto |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (643 pages) |
| Disciplina | 519.50285 |
| Collana | Unitext |
| Soggetto topico |
Mathematical statistics
R (Computer program language) Estadística matemàtica R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-09429-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- How to Use the Text -- Contents -- About the Authors -- 1 Probability -- 1.1 Chance, Chaos and Determinism -- 1.2 Some Basic Terms -- 1.3 The Concept of Probability -- 1.4 Axiomatic Probability -- 1.5 Repeated Trials -- 1.6 Elements of Combinatorial Analysis -- 1.7 Bayes' Theorem -- 1.8 Learning Algorithms -- 1.9 Problems -- 2 Representation of Random Phenomena -- 2.1 Introduction -- 2.2 Random Variables -- 2.3 Cumulative or Distribution Function -- 2.4 Data Representation -- 2.5 Discrete Random Variables -- 2.6 Binomial Distribution -- 2.7 Continuous Random Variables -- 2.8 Mean, Sum of Squares, Variance, Standard Deviation and Quantiles -- 2.9 Operators -- 2.10 Simple Random Sample -- 2.11 Convergence Criteria -- 2.12 Problems -- 3 Basic Probability Theory -- 3.1 Introduction -- 3.2 Properties of the Binomial Distribution -- 3.3 Poisson Distribution -- 3.4 Normal or Gaussian Density -- 3.5 The Three-Sigma Law and the Standard Gaussian Density -- 3.6 Central Limit Theorem and Universality of the GaussianCurve -- 3.7 Poisson Stochastic Processes -- 3.8 χ2 Density -- 3.9 Uniform Density -- 3.10 Chebyshev's Inequality -- 3.11 How to Use Probability Calculus -- 3.12 Problems -- 4 Multivariate Probability Theory -- 4.1 Introduction -- 4.2 Multivariate Statistical Distributions -- 4.3 Covariance and Correlation -- 4.4 Two-Dimensional Gaussian Distribution -- 4.5 The General Multidimensional Case -- 4.6 Multivariate Probability Regions -- 4.7 Multinomial Distribution -- 4.8 Problems -- 5 Functions of Random Variables -- 5.1 Introduction -- 5.2 Functions of a Random Variable -- 5.3 Functions of Several Random Variables -- 5.4 Mean and Variance Transformation -- 5.5 Means and Variances for n Variables -- 5.6 Problems -- 6 Basic Statistics: Parameter Estimation -- 6.1 Introduction -- 6.2 Confidence Intervals.
6.3 Confidence Intervals with Pivotal Variables -- 6.4 Mention of the Bayesian Approach -- 6.5 Some Notations -- 6.6 Probability Estimation -- 6.7 Probability Estimation from Large Samples -- 6.8 Poissonian Interval Estimation -- 6.9 Mean Estimation from Large Samples -- 6.10 Variance Estimation from Large Samples -- 6.11 Mean and Variance Estimation for Gaussian Samples -- 6.12 How to Use the Estimation Theory -- 6.13 Estimates from a Finite Population -- 6.14 Histogram Analysis -- 6.15 Estimation of the Correlation -- 6.16 Problems -- 7 Basic Statistics: Hypothesis Testing -- 7.1 Testing One Hypothesis -- 7.2 The Gaussian z-Test -- 7.3 Student's t-Test -- 7.4 Chi-Square Test -- 7.5 Compatibility Check Between Sample and Population -- 7.6 Hypothesis Testing with Contingency Tables -- 7.7 Multiple Tests -- 7.8 Snedecor's F-Test -- 7.9 Analysis of Variance (ANOVA) -- 7.10 Two-Way ANOVA -- 7.11 Problems -- 8 Monte Carlo Methods -- 8.1 Introduction -- 8.2 What Is Monte Carlo? -- 8.3 Mathematical Aspects -- 8.4 Generation of Discrete Random Variables -- 8.5 Generation of Continuous Random Variables -- 8.6 Linear Search Method -- 8.7 Rejection Method -- 8.8 Particular Random Generation Methods -- 8.9 Monte Carlo Analysis of Distributions -- 8.10 Evaluation of Confidence Intervals -- 8.11 Simulation of Counting Experiments -- 8.12 Non-parametric Bootstrap -- 8.13 Hypothesis Test with Simulated Data -- 8.14 Problems -- 9 Applications of Monte Carlo Methods -- 9.1 Introduction -- 9.2 Study of Diffusion Phenomena -- 9.3 Simulation of Stochastic Processes -- 9.4 Number of Workers in a Plant: Synchronous Simulation -- 9.5 Number of Workers in a Plant: Asynchronous Simulation -- 9.6 Kolmogorov-Smirnov Test -- 9.7 Metropolis Algorithm -- 9.8 Ising Model -- 9.9 Definite Integral Calculation -- 9.10 Importance Sampling -- 9.11 Stratified Sampling. 9.12 Multidimensional Integrals -- 9.13 Problems -- 10 Statistical Inference and Likelihood -- 10.1 Introduction -- 10.2 Maximum Likelihood (ML) Method -- 10.3 Estimator Properties -- 10.4 Theorems on Estimators -- 10.5 Confidence Intervals -- 10.6 Least Squares Method and Maximum Likelihood -- 10.7 Best Fit of Densities to Data and Histograms -- 10.8 Weighted Mean -- 10.9 Test of Hypotheses -- 10.10 One- or Two-Sample Tests -- 10.11 Most Powerful Tests -- 10.12 Test Functions -- 10.13 Sequential Tests -- 10.14 Problems -- 11 Least Squares -- 11.1 Introduction -- 11.2 No Errors on Predictors -- 11.3 Errors in Predictors -- 11.4 Least Squares Regression Lines: Unweighted Case -- 11.5 Unweighted Linear Least Squares -- 11.6 Weighted Linear Least Squares -- 11.7 Properties of Least Squares Estimates -- 11.8 Model Testing and Search for Functional Forms -- 11.9 Search for Correlations -- 11.10 Fit Strategies -- 11.11 Nonlinear Least Squares -- 11.12 Problems -- 12 Experimental Data Analysis -- 12.1 Introduction -- 12.2 Terminology -- 12.3 Constant and Variable Physical Quantities -- 12.4 Instrumental Sensitivity and Accuracy -- 12.5 Measurement Uncertainty -- 12.6 Treatment of Systematic Effects -- 12.7 Best Fit with Offset Systematic Errors -- 12.8 Best Fit with Scale Systematic Errors -- 12.9 Indirect Measurements and Error Propagation -- 12.10 Measurement Types -- 12.11 M(0, 0, Δ) Measurements -- 12.12 M(0, σ, 0) Measurements -- 12.13 M(0, σ, Δ) Measurements -- 12.14 M(f, 0, 0) Measurements -- 12.15 M(f, σ, 0), M(f, 0, Δ) and M(f, σ, Δ) Measurements -- 12.16 A Case Study: Millikan's Experiments -- 12.17 Some Remarks on the Scientific Method -- 12.18 Problems -- A Table of Symbols -- B R Software -- C Moment-Generating Functions -- D Solutions of Problems -- E Tables -- E.1 Integral of the Gaussian Density. E.2 Quantiles of the Student's Density -- E.3 Integrals of the Reduced χ2 Density -- E.4 Quantile Values of the Non-Reduced χ2 Density -- E.5 Quantiles of the F Density -- Bibliography -- Index. |
| Record Nr. | UNINA-9910634035603321 |
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Rotondi Alberto
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of SSDBM 2015 : proceedings of the 27th International Conference on Scientific and Statistical Database Management : June 29-July 1, 2015, San Diego, USA / / editors, Amarnath Gupta, Susan Rathbun
| Proceedings of SSDBM 2015 : proceedings of the 27th International Conference on Scientific and Statistical Database Management : June 29-July 1, 2015, San Diego, USA / / editors, Amarnath Gupta, Susan Rathbun |
| Pubbl/distr/stampa | New York : , : ACM, , 2015 |
| Descrizione fisica | 1 online resource (390 pages) |
| Disciplina | 519.50285 |
| Collana | ACM International Conference Proceedings Series |
| Soggetto topico |
Mathematical statistics - Data processing
Database management Science - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-4503-3709-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
Proceedings of the 27th International Conference on Scientific and Statistical Database Management
Proceedings of Scientific and Statistical Database Management 2015 |
| Record Nr. | UNINA-9910376595403321 |
| New York : , : ACM, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Qualitative comparative analysis with R [[electronic resource] ] : a user’s guide / / by Alrik Thiem, Adrian Dusa
| Qualitative comparative analysis with R [[electronic resource] ] : a user’s guide / / by Alrik Thiem, Adrian Dusa |
| Autore | Thiem Alrik |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (108 p.) |
| Disciplina |
320.01
519.50285 |
| Collana | SpringerBriefs in Political Science |
| Soggetto topico |
Political science
Social sciences Statistics R (Computer program language) Political Science Social Sciences, general Statistics for Social Sciences, Humanities, Law |
| ISBN |
1-283-62433-8
9786613936783 1-4614-4584-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1.Loading Neccessary Packages -- 2. Reading Data into R -- 3. Testing for Neccessity -- 4. Testing for Sufficiency 5 -- Sufficiency: Parameters of Fit 6 -- Plotting Results. |
| Record Nr. | UNINA-9910438352903321 |
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Thiem Alrik
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| New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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SAS for finance : forecasting and data analysis techniques with real-world examples to build powerful financial models / / Harish Gulati
| SAS for finance : forecasting and data analysis techniques with real-world examples to build powerful financial models / / Harish Gulati |
| Autore | Gulati Harish |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham ; ; Mumbai : , : Packt, , 2018 |
| Descrizione fisica | 1 online resource (1 volume) : illustrations |
| Disciplina | 519.50285 |
| Soggetto topico | SAS (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-78862-248-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910466657203321 |
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Gulati Harish
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| Birmingham ; ; Mumbai : , : Packt, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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