Introduction to Statistics and Data Analysis


Author: Roxy Peck,Chris Olsen,Jay L. Devore
Publisher: Cengage Learning
ISBN: 0840054904
Category: Mathematics
Page: 944
View: 9635

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Roxy Peck, Chris Olsen, and Jay Devore's new edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps students grasp concepts and cement their comprehension. Hands-on activities and interactive applets allow students to practice statistics firsthand. INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 4th Edition, includes updated coverage of the graphing calculator as well as expanded coverage of probability. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Introduction to Statistics and Data Analysis

With Exercises, Solutions and Applications in R
Author: Christian Heumann,Michael Schomaker,Shalabh
Publisher: Springer
ISBN: 3319461621
Category: Mathematics
Page: 456
View: 8572

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This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

Introduction to Statistics and Data Analysis, Enhanced Review Edition


Author: Roxy Peck,Chris Olsen,Jay Devore
Publisher: Cengage Learning
ISBN: 0495557838
Category: Mathematics
Page: 880
View: 9510

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Roxy Peck, Chris Olsen and Jay Devore’s new edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. The Third Edition includes coverage of the graphing calculator and includes expanded coverage of probability. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. It helps students grasp concepts and cement their comprehension by using simple notation-frequently substituting words for symbols. Hands-on activities and interactive applets allow students to practice statistics firsthand. This Enhanced Edition includes new Teaching Tips for each chapter in the book, specific references to other available instructor resources, and suggestions for effectively teaching an Advanced Placement Introduction to Statistics course. Also, Enhanced WebAssign now complements a robust supplement package. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

An Introduction to Statistical Methods and Data Analysis


Author: R. Lyman Ott,Micheal T. Longnecker
Publisher: Cengage Learning
ISBN: 1305465520
Category: Mathematics
Page: 1296
View: 7543

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Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Seventh Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

An Introduction to Statistics with Python

With Applications in the Life Sciences
Author: Thomas Haslwanter
Publisher: Springer
ISBN: 3319283162
Category: Computers
Page: 278
View: 2034

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This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.

Einführung in Statistik und Messwertanalyse für Physiker

Monographie
Author: G. Bohm,G. Zech
Publisher: N.A
ISBN: 9783540257592
Category:
Page: 400
View: 4393

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Die Einf]hrung in die Statistik und Messwertanalyse f]r Physiker richtet sich weniger an mathematischen \berlegungen aus, sondern stellt die praktische Anwendung in den Vordergrund und schdrft die Intuition experimentelle Ergebnisse richtig einzuschdtzen. Zahlreiche ausf]hrlich betrachtete Beispiele dienen dazu, hdufig bei der Datenanalyse gemachte Fehler zu vermeiden (unsinnige Anwendung des Chi-Quadrattests, Funktionenanpassung bei falscher Parametrisierung, Entfaltung mit willk]rlicher Regularisierung). Ein besonderes Augenmerk wird auf den Vergleich von Daten mit Monte-Carlo-Simulationen gelenkt. Moderne Experimente kommen nicht ohne Simulation aus. Deshalb ist es wichtig zu wissen, wie Parameteranpassungen und Entfaltungen in diesem Fall durchgef]rt werden. Au_erdem werden den Studierenden moderne Entwicklungen der Statistik nahegebracht, die in dlteren Lehrb]chern nicht behandelt werden.

Introduction to Statistics and Data Analysis

For the Behavioral Sciences
Author: Robert S. Lockhart
Publisher: Macmillan
ISBN: 9780716729747
Category: Psychology
Page: 651
View: 966

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In Introduction to Statistics and Data Analysis, Bob Lockhart emphasizes the link between statistical techniques and scientific discovery by focusing on evaluation and comparison of models. It is an intuitive view of statistics that views all methods as variants on a basic theme (evaluating models). Lockhart's realistic approach enables students to examine and question the methods and goals of statistics and to draw clear connections between statistical methods and the research process.

Introduction to Statistics

Fundamental Concepts and Procedures of Data Analysis
Author: Howard M. Reid
Publisher: SAGE Publications
ISBN: 1483324281
Category: Social Science
Page: 632
View: 4448

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Using a truly accessible and reader-friendly approach, Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis, by Howard M. Reid, redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R

Statistics in the Large
Author: Thomas W. MacFarland
Publisher: Springer Science & Business Media
ISBN: 3319025325
Category: Medical
Page: 167
View: 3443

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Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R. Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.

Introduction to Research Methods and Data Analysis in Psychology


Author: Darren Langdridge,Gareth Hagger-Johnson
Publisher: Pearson Education
ISBN: 9780131982031
Category: Psychology
Page: 558
View: 5324

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This is a comprehensive introduction to research methods and data analysis. The book assumes no previous knowledge of research methods or psychology and provides an accessible and jargon-free way into this frequently difficult topic area.

Statistik-Workshop für Programmierer


Author: Allen B. Downey
Publisher: O'Reilly Germany
ISBN: 3868993436
Category: Computers
Page: 160
View: 322

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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.

Introduction to Statistics and Data Analysis, AP* Edition


Author: Roxy Peck,Chris Olsen,Jay Devore
Publisher: Cengage Learning
ISBN: 9781439047491
Category: Mathematics
Page: 896
View: 4547

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Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Statistical Methods for Data Analysis in Particle Physics


Author: Luca Lista
Publisher: Springer
ISBN: 331920176X
Category: Science
Page: 172
View: 1302

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This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.

Introduction to Statistical Data Analysis for the Life Sciences, Second Edition


Author: Claus Thorn Ekstrom,Helle Sørensen
Publisher: CRC Press
ISBN: 1482238934
Category: Mathematics
Page: 526
View: 7286

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A Hands-On Approach to Teaching Introductory Statistics Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets. New to the Second Edition A new chapter on non-linear regression models A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken Additional exercises in most chapters A summary of statistical formulas related to the specific designs used to teach the statistical concepts This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.

Introduction to Statistical Analysis of Laboratory Data


Author: Alfred Bartolucci,Karan P. Singh,Sejong Bae
Publisher: John Wiley & Sons
ISBN: 1118736834
Category: Mathematics
Page: 256
View: 9674

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Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions

An Introduction to Statistical Methods and Data Analysis


Author: R. Ott,Micheal Longnecker
Publisher: Nelson Education
ISBN: 1111779988
Category: Mathematics
Page: 1296
View: 5464

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Ott and Longnecker’s AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and in news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

An Introduction to Survey Research, Polling, and Data Analysis


Author: Herbert Weisberg,Jon A. Krosnick,Bruce D. Bowen
Publisher: SAGE
ISBN: 9780803974029
Category: Political Science
Page: 394
View: 7129

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This book describes how surveys are conducted in such a way that they can be believed, explains how to read statistical reports and analyze data, and provides guidelines that are useful in evaluating polls. Using examples from contemporary large surveys and polls, as well as from the media, the authors stress the importance of understanding tables thoroughly before moving to interval statistics. In addition, they cover: the design of surveys; the steps for sampling and question writing; interviewing and coding strategies; survey analysis from frequency distributions and cross-tabulations through to control tables and correlation/regression; the ethics of survey research; and how to read and write reports of survey research.

Introduction to the Statistical Analysis of Categorical Data


Author: Erling B. Andersen
Publisher: Springer Science & Business Media
ISBN: 364259123X
Category: Mathematics
Page: 265
View: 2600

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This book deals with the analysis of categorical data. Statistical models, especially log-linear models for contingency tables and logistic regression, are described and applied to real life data. Special emphasis is given to the use of graphical methods. The book is intended as a text for both undergraduate and graduate courses for statisticians, applied statisticians, social scientists, economists and epidemiologists. Many examples and exercises with solutions should help the reader to understand the material.

An Introduction to Statistics and Data Analysis Using Stata®

From Research Design to Final Report
Author: Lisa Daniels,Nicholas Minot
Publisher: SAGE Publications, Incorporated
ISBN: 9781506371832
Category: Social Science
Page: 400
View: 3727

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An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.