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Applied Statistical Learning : With Case Studies in Stata / / by Matthias Schonlau
| Applied Statistical Learning : With Case Studies in Stata / / by Matthias Schonlau |
| Autore | Schonlau Matthias |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource |
| Disciplina | 006.31 |
| Collana | Statistics and Computing |
| Soggetto topico |
Machine learning
Social sciences - Statistical methods Statistics Statistics - Computer programs Quantitative research Statistical Learning Machine Learning Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistics in Business, Management, Economics, Finance, Insurance Statistical Software Data Analysis and Big Data |
| ISBN |
9783031333903
303133390X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- 1 Prologue -- 2 Statistical Learning: Concepts -- 3 Statistical Learning: Practical Aspects -- 4 Logistic Regression -- 5 Lasso and Friends -- 6 Working with Text Data -- 7 Nearest Neighbors -- 8 The Naive Bayes Classifier -- 9 Trees -- 10 Random Forests -- 11 Boosting -- 12 Support Vector Machines -- 13 Feature Engineering -- 14 Neural Networks -- 15 Stacking -- Index. |
| Record Nr. | UNINA-9910736996503321 |
Schonlau Matthias
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied Time Series Analysis and Forecasting with Python [[electronic resource] /] / by Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python [[electronic resource] /] / by Changquan Huang, Alla Petukhina |
| Autore | Huang Changquan |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (377 pages) |
| Disciplina | 813 |
| Collana | Statistics and Computing |
| Soggetto topico |
Time-series analysis
Statistics - Computer programs Econometrics Python (Computer program language) Machine learning Statistics Time Series Analysis Statistical Software Python Machine Learning Statistics in Business, Management, Economics, Finance, Insurance Anàlisi de sèries temporals Python (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-13584-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Time Series Concepts and Python -- 2. Exploratory Time Series Data Analysis -- 3. Stationary Time Series Models -- 4. ARMA and ARIMA Modeling and Forecasting -- 5. Nonstationary Time Series Models -- 6. Financial Time Series and Related Models -- 7. Multivariate Time Series Analysis -- 8. State Space Models and Markov Switching Models -- 9. Nonstationarity and Cointegrations -- 10. Modern Machine Learning Methods for Time Series Analysis. |
| Record Nr. | UNISA-996495169403316 |
|
Huang Changquan
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applied Time Series Analysis and Forecasting with Python / / by Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python / / by Changquan Huang, Alla Petukhina |
| Autore | Huang Changquan |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (377 pages) |
| Disciplina |
813
519.55 |
| Collana | Statistics and Computing |
| Soggetto topico |
Time-series analysis
Statistics - Computer programs Econometrics Python (Computer program language) Machine learning Statistics Time Series Analysis Statistical Software Python Machine Learning Statistics in Business, Management, Economics, Finance, Insurance Anàlisi de sèries temporals Python (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-13584-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Time Series Concepts and Python -- 2. Exploratory Time Series Data Analysis -- 3. Stationary Time Series Models -- 4. ARMA and ARIMA Modeling and Forecasting -- 5. Nonstationary Time Series Models -- 6. Financial Time Series and Related Models -- 7. Multivariate Time Series Analysis -- 8. State Space Models and Markov Switching Models -- 9. Nonstationarity and Cointegrations -- 10. Modern Machine Learning Methods for Time Series Analysis. |
| Record Nr. | UNINA-9910619280803321 |
|
Huang Changquan
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification and Data Science in the Digital Age / / edited by Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent
| Classification and Data Science in the Digital Age / / edited by Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent |
| Autore | Brito Paula |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (393 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
DiasJosé G
LausenBerthold MontanariAngela NugentRebecca |
| Collana | Studies in Classification, Data Analysis, and Knowledge Organization |
| Soggetto topico |
Artificial intelligence - Data processing
Machine learning Data mining Multivariate analysis Statistics - Computer programs Data Science Statistical Learning Machine Learning Data Mining and Knowledge Discovery Multivariate Analysis Statistical Software |
| ISBN | 3-031-09034-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- R. Abdesselam: A Topological Clustering of Individuals -- C. Anton and I. Smith: Model Based Clustering of Functional Data with Mild Outliers -- F. Antonazzo and S. Ingrassia: A Trivariate Geometric Classification of Decision Boundaries for Mixtures of Regressions -- E. Arnone, E. Cunial, and L. M. Sangalli: Generalized Spatio-temporal Regression with PDE Penalization -- R. Ascari and S. Migliorati: A New Regression Model for the Analysis of Microbiome Data -- R. Aschenbruck, G. Szepannek, and A. F. X. Wilhelm: Stability of Mixed-type Cluster Partitions for Determination of the Number of Clusters -- A. Ashofteh and P. Campos: A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment -- V. Batagelj: Clustering and Blockmodeling Temporal Networks – Two Indirect Approaches -- R. Boutalbi, L. Labiod, and M. Nadif: Latent Block Regression Model -- N. Chabane, M. Achraf Bouaoune, R. Amir Sofiane Tighilt, B. Mazoure, N. Tahiri, and V. Makarenkov: Using Clustering and Machine Learning Methods to Provide Intelligent Grocery Shopping Recommendations -- T. Chadjipadelis and S. Magopoulou: COVID-19 Pandemic: a Methodological Model for the Analysis of Government’s Preventing Measures and Health Data Records -- J. Champagne Gareau, É. Beaudry, and V. Makarenkov: pcTVI: Parallel MDP Solver Using a Decomposition into Independent Chains -- C. Di Nuzzo and S. Ingrassia: Three-way Spectral Clustering -- J. Dobša and H. A. L. Kiers: Improving Classification of Documents by Semi-supervised Clustering in a Semantic Space -- J. Gama: Trends in Data Stream Mining -- L. A. García-Escudero, A. Mayo-Iscar, G. Morelli, and M. Riani: Old and New Constraints in Model Based Clustering -- V. G Genova, G. Giordano, G . Ragozini, and M. Prosperina Vitale: Clustering Student Mobility Data in 3-way Networks -- R. Giubilei: Clustering Brain Connectomes Through a Density-peak Approach -- T. Górecki, M. Šuczak, and P. Piasecki: Similarity Forest for Time Series Classification -- K. Hayashi, E. Hoshino, M. Suzuki, E. Nakanishi, K. Sakai, and M. Obatake: Detection of the Biliary Atresia Using Deep Convolutional Neural Networks Based on Statistical Learning Weights via Optimal Similarity and Resampling Methods -- Ch. Hennig: Some Issues in Robust Clustering -- J. Kalina and P. Janá£ek: Robustness Aspects of Optimized Centroids -- L. Labiod and M. Nadif: Data Clustering and Representation Learning Based on Networked Data -- Lazhar Labiod and Mohamed Nadif: Towards a Bi-stochastic Matrix Approximation of k-means and Some Variants -- A. LaLonde, T. Love, D. R. Young, and T. Wu: Clustering Adolescent Female Physical Activity Levels with an Infinite Mixture Model on Random Effects -- Á. López-Oriona, J. A. Vilar, and P. D’Urso: Unsupervised Classification of Categorical Time Series Through Innovative Distances -- D. Masís, E. Segura, J. Trejos, and A. Xavier: Fuzzy Clustering by Hyperbolic Smoothing -- R. Meng, H. K. H. Lee, and K. Bouchard: Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Networks -- H. Duy Nguyen, F. Forbes, G. Fort, and O. Cappé: An Online Minorization-Maximization Algorithm -- L. Palazzo and R. Ievoli: Detecting Differences in Italian Regional Health Services During Two Covid-19 Waves -- G. Panagiotidou and T. Chadjipadelis: Political and Religion Attitudes in Greece: Behavioral Discourses -- K. Pawlasová, I. Karafiátová, and J. Dvořák: Supervised Classification via Neural Networks for Replicated Point Patterns -- G. Perrone and G. Soffritti: Parsimonious Mixtures of Seemingly Unrelated Contaminated Normal Regression Models -- N. Pronello, R. Ignaccolo, L. Ippoliti, and S. Fontanella: Penalized Model-based Functional Clustering: a Regularization Approach via Shrinkage Methods -- D. Rodrigues, L. P. Reis, and B. M. Faria: Emotion Classification Based on Single Electrode Brain Data: Applications for Assistive Technology -- R. Scimone, A. Menafoglio, L. M. Sangalli, and P. Secchi: The Death Process in Italy Before and During the Covid-19 Pandemic: a Functional Compositional Approach -- O. Silva, Á. Sousa, and H. Bacelar-Nicolau: Clustering Validation in the Context of Hierarchical Cluster Analysis: an Empirical Study -- C. Silvestre, M. G. M. S. Cardoso, and M. Figueiredo: An MML Embedded Approach for Estimating the Number of Clusters -- Á. Sousa, O. Silva, M. Graça Batista, S. Cabral, and H. Bacelar-Nicolau: Typology of Motivation Factors for Employees in the Banking Sector: An Empirical Study Using Multivariate Data Analysis Methods -- J. Michael Spoor, J. Weber, and J. Ovtcharova: A Proposal for Formalization and Definition of Anomalies in Dynamical Systems -- N. Tahiri and A. Koshkarov: New Metrics for Classifying Phylogenetic Trees Using -means and the Symmetric Difference Metric -- S. D. Tomarchio: On Parsimonious Modelling via Matrix-variate t Mixtures -- G. Zammarchi, M. Romano, and C. Conversano: Evolution of Media Coverage on Climate Change and Environmental Awareness: an Analysisof Tweets from UK and US Newspapers. |
| Record Nr. | UNINA-9910768481303321 |
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Brito Paula
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational Finance with R / / by Rituparna Sen, Sourish Das
| Computational Finance with R / / by Rituparna Sen, Sourish Das |
| Autore | Sen Rituparna |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 332.028553 |
| Collana | Indian Statistical Institute Series |
| Soggetto topico |
Statistics
Social sciences - Mathematics Stochastic analysis Machine learning Statistics - Computer programs Statistics in Business, Management, Economics, Finance, Insurance Mathematics in Business, Economics and Finance Stochastic Analysis Machine Learning Statistical Software |
| ISBN | 981-19-2008-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Numerical Methods -- 1. Preliminaries -- 2. Solving a System of Linear Equations -- 3. Solving Non-Linear Equations -- 4. Numerical Integration -- 5. Numerical Differentiation -- 6. Numerical Methods for PDE -- 7. Optimization -- Part II. Simulation Methods -- 8. Monte-Carlo Methods -- 9. Lattice Models -- 10. Simulating Brownian Motion -- 11. Variance Reduction -- 12. Bayesian Computation with Stan -- 13. Resampling -- Part III. Statistical Methods -- 14. Descriptive Methods -- 15. Inferential Statistics -- 16. Statistical Risk Analysis -- 17. Multivariate Analysis -- 18. Univariate Time Series -- 19. Multivariate Time Series -- 20. High Frequency Data -- 21. Supervised Learning -- 22. Unsupervised Learning -- Appendix -- A. Basics of Mathematical Finance -- B. Introduction to R -- C. Extreme Value Theory in Finance -- Bibliography. . |
| Record Nr. | UNINA-9910733712103321 |
|
Sen Rituparna
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A Course on Small Area Estimation and Mixed Models : Methods, Theory and Applications in R / / by Domingo Morales, María Dolores Esteban, Agustín Pérez, Tomáš Hobza
| A Course on Small Area Estimation and Mixed Models : Methods, Theory and Applications in R / / by Domingo Morales, María Dolores Esteban, Agustín Pérez, Tomáš Hobza |
| Autore | Morales Domingo |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XX, 599 p. 373 illus., 10 illus. in color.) |
| Disciplina | 519.52 |
| Collana | Statistics for Social and Behavioral Sciences |
| Soggetto topico |
Social sciences - Statistical methods
Statistics Statistics - Computer programs Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistical Theory and Methods Statistical Software Statistics in Business, Management, Economics, Finance, Insurance |
| ISBN |
9783030637576
3030637573 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Small Area Estimation -- 2 Design-based Direct Estimation -- 3 Design-based Indirect Estimation -- 4 Prediction Theory -- 5 Linear Models -- 6 Linear Mixed Models -- 7 Nested Error Regression Models -- 8 EBLUPs under Nested Error Regression Models -- 9 Mean Squared Error of EBLUPs -- 10 EBPs under Nested Error Regression Models -- 11 EBLUPs under Two-fold Nested Error Regression Models -- 12 EBPs under Two-fold Nested Error Regression Models -- 13 Random Regression Coefficient Models -- 14 EBPs under Unit-level Logit Mixed Models -- 15 EBPs under Unit-level Two-fold Logit Mixed Models -- 16 Fay-Herriot Models -- 17 Area-level Temporal Linear Mixed Models -- 18 Area-level Spatio-temporal Linear Mixed Models -- 19 Area-level Bivariate Linear Mixed Models -- 20 Area-level Poisson Mixed Models -- 21 Area-level Temporal Poisson Mixed Models -- A Some Useful Formulas -- Index. |
| Record Nr. | UNINA-9910484980203321 |
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Morales Domingo
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Elements of Network Science : Theory, Methods and Applications in Stata, R and Python / / by Antonio Zinilli
| Elements of Network Science : Theory, Methods and Applications in Stata, R and Python / / by Antonio Zinilli |
| Autore | Zinilli Antonio |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XVI, 242 p. 89 illus., 77 illus. in color.) |
| Disciplina | 300.727 |
| Collana | Statistics and Computing |
| Soggetto topico |
Social sciences - Statistical methods
Mathematical statistics - Data processing Social sciences - Network analysis Statistics - Computer programs Statistics Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistics and Computing Network Research Statistical Software Statistics in Business, Management, Economics, Finance, Insurance Statistical Theory and Methods |
| ISBN | 3-031-84712-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | - 1. Introduction -- 2. Network Science: concepts and definitions -- 3. Network Metrics -- 4. Theoretical models of networks -- 5.Statistical social network models. |
| Record Nr. | UNINA-9910999790103321 |
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Zinilli Antonio
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910453567003321 |
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Nelson Stephen L.
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| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910790926503321 |
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Nelson Stephen L.
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||
| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910809370903321 |
|
Nelson Stephen L.
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| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
