Essential First Steps to Data Analysis

Scenario-Based Examples Using SPSS
Author: Carol S. Parke
Publisher: SAGE
ISBN: 1412997518
Category: Computers
Page: 265
View: 7584
Carol S. Parke's Essential First Steps to Data Analysis: Scenario-Based Examples Using SPSS provides instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Such preparation may involve data management and manipulation tasks, data organization, structural changes to the data files, or conducting preliminary analysis. Twelve research-based scenarios are used to present the content. Each scenario tells the "story" of a researcher who thoroughly examined their data and the decisions they made along the way. The scenario begins with a description of the researcher's study and his/her data file(s), then describes the issues the researcher must address, explains why they are important, shows how SPSS was used to address the issues and prepare data, and shares the researcher's reflections and any additional decision-making. Finally, each scenario ends with the researcher's written summary of the procedures and outcomes from the initial data preparation or analysis.

Datenanalyse mit Python

Auswertung von Daten mit Pandas, NumPy und IPython
Author: Wes McKinney
Publisher: O'Reilly
ISBN: 3960102143
Category: Computers
Page: 542
View: 5662
Erfahren Sie alles über das Manipulieren, Bereinigen, Verarbeiten und Aufbereiten von Datensätzen mit Python: Aktualisiert auf Python 3.6, zeigt Ihnen dieses konsequent praxisbezogene Buch anhand konkreter Fallbeispiele, wie Sie eine Vielzahl von typischen Datenanalyse-Problemen effektiv lösen. Gleichzeitig lernen Sie die neuesten Versionen von pandas, NumPy, IPython und Jupyter kennen.Geschrieben von Wes McKinney, dem Begründer des pandas-Projekts, bietet Datenanalyse mit Python einen praktischen Einstieg in die Data-Science-Tools von Python. Das Buch eignet sich sowohl für Datenanalysten, für die Python Neuland ist, als auch für Python-Programmierer, die sich in Data Science und Scientific Computing einarbeiten wollen. Daten und zugehöriges Material des Buchs sind auf GitHub verfügbar.Aus dem Inhalt:Nutzen Sie die IPython-Shell und Jupyter Notebook für das explorative ComputingLernen Sie Grundfunktionen und fortgeschrittene Features von NumPy kennenSetzen Sie die Datenanalyse-Tools der pandasBibliothek einVerwenden Sie flexible Werkzeuge zum Laden, Bereinigen, Transformieren, Zusammenführen und Umformen von DatenErstellen Sie interformative Visualisierungen mit matplotlibWenden Sie die GroupBy-Mechanismen von pandas an, um Datensätzen zurechtzuschneiden, umzugestalten und zusammenzufassenAnalysieren und manipulieren Sie verschiedenste Zeitreihen-DatenFür diese aktualisierte 2. Auflage wurde der gesamte Code an Python 3.6 und die neuesten Versionen der pandas-Bibliothek angepasst. Neu in dieser Auflage: Informationen zu fortgeschrittenen pandas-Tools sowie eine kurze Einführung in statsmodels und scikit-learn.

Data Collection and Analysis

Author: Roger Sapsford,Victor Jupp
Publisher: SAGE
ISBN: 0761943625
Category: Social Science
Page: 332
View: 7626
In simple and non-technical terms, this text illustrates a wide range of techniques and approaches used in social research projects.

Handbook of Statistical Analysis and Data Mining Applications

Author: Robert Nisbet,John Elder,Gary Miner
Publisher: Academic Press
ISBN: 9780080912035
Category: Mathematics
Page: 864
View: 9227
The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book

Python Data Science Essentials

Author: Alberto Boschetti,Luca Massaron
Publisher: Packt Publishing Ltd
ISBN: 1786462834
Category: Computers
Page: 378
View: 8209
Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.

Qualitative Data Analysis with NVivo

Author: Patricia Bazeley
Publisher: SAGE
ISBN: 1446234959
Category: Social Science
Page: 232
View: 7571
`In plain language but with very thorough detail, this book guides the researcher who really wants to use the NVivo software (and use it now) into their project. The way is lit with real-project examples, adorned with tricks and tips, but it’s a clear path to a project' - Lyn Richards, Founder and Non-Executive Director, QSR International Doing Qualitative Data Analysis with NVivo is essential reading for anyone thinking of using their computer to help analyze qualitative data. With 15 years experience in computer-assisted analysis of qualitative and mixed-mode data, Patricia Bazeley is one of the leaders in the use and teaching of NVivo software. Through this very practical book, readers are guided on how best to make use of the powerful and flexible tools offered by the latest version of NVivo as they work through each stage of their research projects. Explanations draw on examples from her own and others' projects, and are supported by the methodological literature. Researchers have different requirements and come to their data from different perspectives. This book shows how NVivo software can accommodate and assist analysis across those different perspectives and methodological approaches. It is required reading for both students and experienced researchers alike.

Quantitative Data Analysis with SPSS

Author: Pete Greasley
Publisher: Open University Press
ISBN: 9780335223053
Category: Social Science
Page: 144
View: 8597
"This is an ideal introductory book for budding researchers who are embarking on the development and then analysis of data, and in this case, more specifically questionnaires using partly or exclusively closed questions amenable to statistical analysis." Primary Health Care Research and Development "The text is a welcome addition for nursing students at both undergraduate and postgraduate level research. Having reviewed the text I can only inform you how a student described a chapter in the book recently when she borrowed it. 'The language is clear and unambiguous'. I will be strongly encouraging students to either purchase the text ... with the purpose of giving them a foundation in statistics." William Evans, Institute of Technology Tralee, Ireland This accessible book is essential reading for those looking for a short and simple guide to basic data analysis. Written for the complete beginner, the book is the ideal companion when undertaking quantitative data analysis for the first time using SPSS. The book uses a simple example of quantitative data analysis that would be typical to the health field to take you through the process of data analysis step by step. The example used is a doctor who conducts a questionnaire survey of 30 patients to assess a specific service. The data from these questionnaires is given to you for analysis, and the book leads you through the process required to analyse this data. Handy screenshots illustrate each step of the process so you can try out the analysis for yourself, and apply it to your own research with ease. Topics covered include: Questionnaires and how to analyse them Coding the data for SPSS, setting up an SPSS database and entering the data Descriptive statistics and illustrating the data using graphs Cross-tabulation and the Chi-square statistic Correlation: examining relationships between interval data Examining differences between two sets of scores Reporting the results and presenting the data Quantitative Data Analysis Using SPSS is helpful for any students in health and social sciences with little or no experience of quantitative data analysis and statistics.

First Steps In Research and Statistics

A Practical Workbook for Psychology Students
Author: Dennis Howitt,Duncan Cramer
Publisher: Routledge
ISBN: 1134635494
Category: Psychology
Page: 272
View: 7537
First Steps in Research and Statistics is a new, very accessible approach to learning about quantitative methods. No previous knowledge or experience is assumed and every stage of the research process is covered. Key topics include: * Formulating your research questions * How to choose the right statistical test for your research design * Important research issues, such as questionnaire design, ethics, sampling, reliability and validity * Conducting simple statistics to explore relationships and differences in your data * Using statistics to explore relationships and differences in your data * Writing up your research report and presenting statistics Simple and helpful worksheets and flow diagrams guide you through the research stages. Each chapter contains exercises with answers to check whether you've understood.

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Author: Tailen Hsing,Randall Eubank
Publisher: John Wiley & Sons
ISBN: 0470016914
Category: Mathematics
Page: 480
View: 6676
Functional data is data in the form of curves that is becoming a popular method for interpreting scientific data. Statistical Analysis of Functional Data provides an authoritative account of function data analysis covering its foundations, theory, methodology, and practical implementation. It also contains examples taken from a wide range of disciplines, including finance, medicine, and psychology. The book includes a supporting Web site hosting the real data sets analyzed in the book and related software. Statistical researchers or practitioners analyzing functional data will find this book useful.


Data Analysis for the Laboratory and Chemical Plant
Author: Richard G. Brereton
Publisher: John Wiley & Sons
ISBN: 0470845740
Category: Science
Page: 504
View: 7724
This book is aimed at the large number of people who need to use chemometrics but do not wish to understand complex mathematics, therefore it offers a comprehensive examination of the field of chemometrics without overwhelming the reader with complex mathematics. * Includes five chapters that cover the basic principles of chemometrics analysis. * Provides two chapters on the use of Excel and MATLAB for chemometrics analysis. * Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.

Quantitative Data Analysis with SPSS 12 and 13

A Guide for Social Scientists
Author: Alan Bryman,Professor of Organizational and Social Research Alan Bryman,Duncan Cramer
Publisher: Routledge
ISBN: 1134327153
Category: Psychology
Page: 368
View: 4400
This new edition has been completely updated to accommodate the needs of users of SPSS Release 12 and 13 for Windows, whilst still being applicable to those using SPSS Release 11 and 10. Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS. No previous familiarity with computing or statistics is required to benefit from this step-by-step guide to techniques including: Non-parametric tests Correlation Simple and multiple regression Multivarate analysis of variance and covariance Factor analysis The authors discuss key issues facing the newcomer to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter contains worked examples to illustrate the points raised and ends with a comprehensive range of exercises which allow the reader to test their understanding of the topic. This new edition of this hugely successful textbook will guide the reader through the basics of quantitative data analysis and become an essential reference tool for both students and researchers in the social sciences. The datasets used in Quantitative Data Analysis for SPSS Release 12 and 13 are available online at .

Practical work in undergraduate science

Author: E. R. Davies
Publisher: Heinemann Educational Books
ISBN: 9780435695828
Category: Science
Page: 201
View: 2113

From Data and Information Analysis to Knowledge Engineering

Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005
Author: Myra Spiliopoulou,Rudolf Kruse,Christian Borgelt,Andreas Nürnberger,Wolfgang Gaul
Publisher: Springer Science & Business Media
ISBN: 9783540313137
Category: Language Arts & Disciplines
Page: 761
View: 5889
This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to traditional subjects like Classification, Clustering, and Data Analysis, converage extends to a wide range of topics relating to Computer Science: Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization.

Analysing Economic Data

A Concise Introduction
Author: T. Mills
Publisher: Springer
ISBN: 1137401907
Category: Business & Economics
Page: 297
View: 7985
Covers the key issues required for students wishing to understand and analyse the core empirical issues in economics. It focuses on descriptive statistics, probability concepts and basic econometric techniques and has an accompanying website that contains all the data used in the examples and provides exercises for undertaking original research.

SPSS Survival Manual

A step by step guide to data analysis using SPSS
Author: Julie Pallant
Publisher: Allen & Unwin
ISBN: 1741762421
Category: Reference
Page: 372
View: 763
The SPSS Survival Manual throws a lifeline to students and researchers grappling with the SPSS data analysis software. In this fully revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting SPSS output and an example of how to present the results in a report. For both beginners and experienced SPSS users in psychology, education, business, sociology, health and related disciplines, the SPSS Survival Manual is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. In this third edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output. A new flowchart is included for SPSS procedures, and factor analysis procedures have been streamlined. It includes extra examples and material on syntax. Additional datafiles are available on the book's support website.

Essential Ethnographic Methods

Observations, Interviews, and Questionnaires
Author: Bruce G. Carruthers,Stephen L. Schensul,Jean J. Schensul,Margaret Diane LeCompte,Margaret Diane LeCompte, M.A., Ph.D.
Publisher: Rowman Altamira
ISBN: 9780761991441
Category: Social Science
Page: 318
View: 3540
Essential Ethnographic Methods akes a mixed methods approach to introducing the fundamental, face-to-face data collection tools that ethnographers and other qualitative researchers use.

Advances in Intelligent Data Analysis

4th International Conference, IDA 2001, Cascais, Portugal, September 13-15, 2001. Proceedings
Author: Frank Hoffmann
Publisher: Springer Science & Business Media
ISBN: 3540425810
Category: Business & Economics
Page: 384
View: 7749
Wewouldalsoliketoexpressourgratitudetothesponsors:Fundac˜ ¸ao paraaCiˆenciaeaTecnologia,Minist´eriodaCiˆenciaedaTecnologia,Faculdade deCiˆenciaseTecnologia,UniversidadeNovadeLisboa,Funda¸c˜aoCalousteG- benkianandIPEInvestimentoseParticipac˜ ¸oesEmpresariais,S. A. September2001 FrankHo?mann DavidJ. Hand NiallAdams GabrielaGuimaraes DougFisher Organization IDA2001wasorganizedbythedepartmentofComputerScience,NewUniversity ofLisbon. ConferenceCommittee GeneralChair: DouglasFisher(VanderbiltUniversity,USA) ProgramChairs: DavidJ. Hand(ImperialCollege,UK) NiallAdams(ImperialCollege,UK) ConferenceChair: GabrielaGuimaraes(NewUniversityofLisbon,Portugal) PublicityChair: FrankH¨oppner(Univ. ofAppl. SciencesEmden,Germany) PublicationChair: FrankHo?mann(RoyalInstituteofTechnology,Sweden) LocalChair: FernandoMoura-Pires(UniversityofEvora,Portugal) AreaChairs: RobertaSiciliano(UniversityofNaples,Italy) ArnoSiebes(CWI,TheNetherlands) PavelBrazdil(UniversityofPorto,Portugal) ProgramCommittee NiallAdams(ImperialCollege,UK) PieterAdriaans(Syllogic,TheNetherlands) RussellAlmond(EducationalTestingService,USA) ThomasB¨ack(InformatikCentrumDortmund,Germany) RiccardoBellazzi(UniversityofPavia,Italy) MichaelBerthold(Tripos,USA) LiuBing(NationalUniversityofSingapore) PaulCohen(UniversityofMassachusetts,USA) PaulDarius(LeuvenUniversity,Belgium) FazelFamili(NationalResearchCouncil,Canada) DouglasFisher(VanderbiltUniversity,USA) KarlFroeschl(UniversityofVienna,Austria) AlexGammerman(RoyalHolloway,UK) AdolfGrauel(UniversityofPaderborn,Germany) GabrielaGuimaraes(NewUniversityofLisbon,Portugal) LawrenceO. Hall(UniversityofSouthFlorida,USA) FrankHo?mann(RoyalInstituteofTechnology,Sweden) AdeleHowe(ColoradoStateUniversity,USA) Klaus-PeterHuber(SASInstitute,Germany) DavidJensen(UniversityofMassachusetts,USA) JoostKok(LeidenUniversity,TheNetherlands) RudolfKruse(UniversityofMagdeburg,Germany) FrankKlawonn(UniversityofAppliedSciencesEmden,Germany) VIII Organization HansLenz(FreeUniversityofBerlin,Germany) DavidMadigan(Soliloquy,USA) RainerMalaka(EuropeanMediaLaboratory,Germany) HeikkiMannila(Nokia,Finland) FernandoMouraPires(UniversityofEvora,Portugal) SusanaNascimento(UniversityofLisbon,Portugal) WayneOldford(UniversityofWaterloo,Canada) AlbertPrat(TechnicalUniversityofCatalunya,Spain) PeterProtzel(TechnicalUniversityChemnitz,Germany) GiacomodellaRiccia(UniversityofUdine,Italy) RosannaSchiavo(UniversityofVenice,Italy) KaisaSere(AboAkademiUniversity,Finland) RobertaSiciliano(UniversityofNaples,Italy) RosariaSilipo(Nuance,USA) FloorVerdenius(ATO-DLO,TheNetherlands) StefanWrobel(UniversityofMagdeburg,Germany) HuiXiaoLiu(BrunelUniversity,UK) NevinZhang(HongKongUniversityofScienceandTechnology,HongKong) SponsoringInstitutions Fundac˜ ¸aoparaaCiˆenciaeaTecnologia,Minist´eriodaCiˆenciaedaTecnologia FaculdadedeCiˆenciaseTecnologia,UniversidadeNovadeLisboa Fundac˜ ¸aoCalousteGulbenkian IPEInvestimentoseParticipac˜ ¸oesEmpresariais,S. A. TableofContents TheFourthInternationalSymposiumonIntelligentData Analysis FeatureCharacterizationinScienti?cDatasets. . . . . . . . . . . . . . . . . . . . . . . . . 1 ElizabethBradley(UniversityofColorado),NancyCollins(University ofColorado),W. PhilipKegelmeyer(SandiaNationalLaboratories) RelevanceFeedbackintheBayesianNetworkRetrievalModel: AnApproachBasedonTermInstantiation. . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 LuisM. deCampos(UniversityofGranada),JuanM. Fernan ´ dez–Luna (UniversityofJa´en),JuanF. Huete(UniversityofGranada) GeneratingFuzzySummariesfromFuzzyMultidimensionalDatabases. . . . 24 AnneLaurent(Universit´ePierreetMarieCurie) AMixture-of-ExpertsFrameworkforLearningfromImbalancedData Sets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 AndrewEstabrooks(IBM),NathalieJapkowicz(UniversityofOttawa) PredictingTime-VaryingFunctionswithLocalModels. . . . . . . . . . . . . . . . . . 44 AchimLewandowski(ChemnitzUniversity),PeterProtzel(Chemn

Essential Programming for Linguistics

Author: Martin Weisser
Publisher: Edinburgh University Press
ISBN: 0748641831
Category: Computers
Page: 184
View: 5406
A gentle introduction to programming for students and researchers interested in conducting computer-based analysis in linguistics, this book is an ideal starting point for linguists approaching programming for the first time. Assuming no background knowledge of programming, the author introduces basic notions and techniques needed for linguistics programming and helps readers to develop their understanding of electronic texts.The book includes many examples based on diverse topics in linguistics in order to demonstrate the applicability of the concepts at the heart of programming. Practical examples are designed to help the reader to:*Identify basic issues in handling language data, including Unicode processing*Conduct simple analyses in morphology/morphosyntax, and phonotactics*Understanding techniques for matching linguistic patterns*Learn to convert data into formats and data structures suitable for linguistic analysis*Create frequency lists from corpus materials to gather basic descriptive statistics on texts*Understand, obtain and 'clean up' web-based data*Design graphical user interfaces for writing more efficient and easy-to-use analysis tools.Two different types of exercise help readers to either learn to interpret and understand illustrative sample code, or to develop algorithmic thinking and solution strategies through turning a series of instructions into sample programs. Readers will be equipped with the necessary tools for designing their own extended projects.Key Features:*Ideal introduction for students of linguistics attempting to process corpus materials or literary texts for dissertations, theses or advanced research work*Linguistic examples throughout the text clearly demonstrate the application of programming theory and techniques*Coverage ranging from basic to more complex topics and methodologies enables the reader to progress at their own pace*Two chapters on the advantages of modularity and associated issues provid

Springer Handbook of Engineering Statistics

Author: Hoang Pham
Publisher: Springer Science & Business Media
ISBN: 1852338067
Category: Business & Economics
Page: 1120
View: 1401
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.

Statistik-Workshop für Programmierer

Author: Allen B. Downey
Publisher: O'Reilly Germany
ISBN: 3868993436
Category: Computers
Page: 160
View: 7511
Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.