Eda Explorative Datenanalyse

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Exploratory Data Analysis

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Author : Frederick Hartwig
language : en
Publisher: SAGE
Release Date : 1979

Exploratory Data Analysis written by Frederick Hartwig and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Electronic books categories.

An introduction to the underlying principles, central concepts, and basic techniques for conducting and understanding exploratory data analysis - with numerous social science examples.

Eda Explorative Datenanalyse

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Author : Wolfgang Polasek
language : de
Publisher: Springer-Verlag
Release Date : 2013-03-07

Eda Explorative Datenanalyse written by Wolfgang Polasek and has been published by Springer-Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-07 with Business & Economics categories.

Explorative Datenanalyse (EDA), deskriptive Statistik und graphische Darstellungstechnik werden unter einem gemeinsamen Aspekt beschrieben. Dem Studenten im ersten Studienjahr soll damit bereits möglichst früh ein Überblick über die verschiedenen Typen der statistischen Modellierung geboten werden. Das Buch präsentiert resistente statistische Methoden, aber ohne deren wahrscheinlichkeitstheoretische oder induktive Begründung. An mehreren Beispielen aus den Sozial- und Wirtschaftswissenschaften wird gezeigt, wie ein deskriptiver Modellbildungsprozeß mit einfachen Mitteln möglich ist.

Hands On Exploratory Data Analysis With Python

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Author : Suresh Kumar Mukhiya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-03-27

Hands On Exploratory Data Analysis With Python written by Suresh Kumar Mukhiya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-27 with Computers categories.

Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.

Applications Basics And Computing Of Exploratory Data Analysis

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Author : Paul F. Velleman
language : en
Publisher:
Release Date : 1981

Applications Basics And Computing Of Exploratory Data Analysis written by Paul F. Velleman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Mathematics categories.

Stem-and-left displays; Letter-value displays; Boxplots; x-y plotting; Resistant line; Smoothing data; Coded tables; Median polish; Rootograms; Computer graphics; Utility programs; Programming conventions; Minitab implementation; Appendices; Index.

Exploratory Data Analysis

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Author : John Wilder Tukey
language : en
Publisher: Addison-Wesley Publishing Company
Release Date : 1977

Exploratory Data Analysis written by John Wilder Tukey and has been published by Addison-Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Mathematics categories.

This book serves as an introductory text for exploratory data analysis. It exposes readers and users to a variety of techniques for looking more effectively at data. The emphasis is on general techniques, rather than specific problems.

Exploratory Data Analysis With Matlab

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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2004-11-29

Exploratory Data Analysis With Matlab written by Wendy L. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11-29 with Business & Economics categories.

Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger a

Eda Explorative Datenanalyse

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Author : Peter Hauke
language : de
Publisher:
Release Date : 1998

Eda Explorative Datenanalyse written by Peter Hauke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.

Exploratory Analysis Of Spatial And Temporal Data

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Author : Natalia Andrienko
language : en
Publisher: Springer
Release Date : 2016-04-01

Exploratory Analysis Of Spatial And Temporal Data written by Natalia Andrienko and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-01 with categories.

Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. As something relevant is detected in data, new questions arise, causing specific parts to be viewed in more detail. So EDA has a significant appeal: it involves hypothesis generation rather than mere hypothesis testing. The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular. They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks. This typology is then applied to the description of existing approaches and technologies, resulting not just in recommendations for choosing methods but in a set of generic procedures for data exploration. Professionals practicing analysis will profit from tested solutions - illustrated in many examples - for reuse in the catalogue of techniques presented. Students and researchers will appreciate the detailed description and classification of exploration techniques, which are not limited to spatial data only. In addition, the general principles and approaches described will be useful for designers of new methods for EDA.

Explorative Daten Analyse

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Author : Wolfgang Polasek
language : de
Publisher: Springer-Verlag
Release Date : 2013-03-08

Explorative Daten Analyse written by Wolfgang Polasek and has been published by Springer-Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-08 with Mathematics categories.

In diesem Buch wird die deskriptive Statistik im weitesten Sinne behandelt. Explorative Datenanalyse (EDA), deskriptive Statistik und graphische Darstellungstechnik werden unter einem gemeinsamen Aspekt beschrieben. Das Buch versucht, erstmals in deutscher Sprache, die Datenaufbereitung im Stile Tukey (1977) und Mosteller und Tukey (1977) mit Beispielen aus dem sozial- und wirtschaftswissenschaftlichen Bereich dem Studenten nahezubringen. Dabei wird vollständig auf den Gebrauch von Wahrscheinlichkeiten verzichtet, dafür aber der Begriff der empirischen Verteilung zentral behandelt. Darüberhinaus wird eine Brücke zwischen der traditionellen (deutschsprachigen) deskriptiven Statistik und dem neuen explorativen Zugang des angelsächsischen Raumes geschlagen. Schließlich wird in jedem Kapital die Verfügbarkeit der Methoden in Programmpaketen kurz diskutiert.

Understanding Robust And Exploratory Data Analysis

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Author : David C. Hoaglin
language : en
Publisher:
Release Date : 1983

Understanding Robust And Exploratory Data Analysis written by David C. Hoaglin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematics categories.

Textbook on robust and exploratory data analysis and related statistical methods - covers stem-and-leaf displays, letter values, boxplots and batch graphic displays, resistant lines, analysis of two- way tables by medians, examining residuals, mathematical aspects of transformation, scale estimators, comparison of location estimators, confidence intervals for location, etc. References.