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| spss 17.0 guide to data analysis: SPSS Statistics 17.0 Guide to Data Analysis Marija J. Norušis, 2008 TheSPSS 17.0 Guide to Data Analysisis a friendly introduction to both data analysis and SPSS, the world’s leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With the this book, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS. Author Marija Norušis incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners. These data are used throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun! A data CD-ROM is included with this book. |
| spss 17.0 guide to data analysis: IBM SPSS Statistics 19 Guide to Data Analysis Marija J. Norušis, 2011 The PASW Statistics 19 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 19 (formerly SPSS Statistics), the world's leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With this book, you'll learn how to describe data, test hypotheses, and examine relationships using PASW. Author Marija Noru is incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners, throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun! A data CD-ROM is included with this book. |
| spss 17.0 guide to data analysis: Visual Approach to SPSS for Windows, A: A Guide to SPSS 17.0 Leonard D Stern, 2013-08-28 For courses on SPSS. SPSS is, essentially, a visually-driven program, but most texts rely primarily on a verbal approach to describe its use. A Visual Approach to SPSS for Windows is the first text of its kind to employ what the author refers to as “visual sequencing” to teach students how to use SPSS. |
| spss 17.0 guide to data analysis: Interpreting Quantitative Data with SPSS Rachad Antonius, 2003-01-22 This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied. |
| spss 17.0 guide to data analysis: IBM SPSS Statistics 27 Step by Step Darren George, Paul Mallery, 2021 IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. This book covers the basics of statistical analysis and addresses more advanced topics such as multidimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA (between- and within-subjects), cluster analysis, Log-linear models, logistic regression, and a chapter describing residuals. The end sections include a description of data files used in exercises, an exhaustive glossary, suggestions for further reading, and a comprehensive index. IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an invaluable aid to thousands of researchers and students. New to this edition: Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 27 A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection. |
| spss 17.0 guide to data analysis: Quantitative Data Analysis with IBM SPSS 17, 18 & 19 Alan Bryman, Duncan Cramer, 2012-08-21 This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16. As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available to them. No previous experience of statistics or computing is required as this book provides a step-by-step guide to statistical techniques, including: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis. This book comes equipped with a comprehensive range of exercises for further practice, and it covers key issues such as sampling, statistical inference, conceptualization and measurement and selection of appropriate tests. The authors have also included a helpful glossary of key terms. The data sets used in Quantitative Data Analysis with IBM SPSS 17, 18 and 19 are available online at http://www.routledgetextbooks.com/textbooks/_author/bryman-9780415579193/; in addition, a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available free of charge to lecturers who adopt the book. |
| spss 17.0 guide to data analysis: SPSS 17.0 - For Researchers S. L. Gupta, Hitesh Gupta, 2011 |
| spss 17.0 guide to data analysis: SPSS 10.0 Guide to Data Analysis Marija J. Norušis, 2000 For introductory courses in data analysis and SPSS. Can also be used as a supplement for introductory and business statistics. This friendly, easy-to-understand introduction enables students to get a jump start on describing data, testing hypotheses, and examining relationships using SPSS. A combination of examples, exercises, and data files gives readers hands-on experience finding meaning in data. |
| spss 17.0 guide to data analysis: SPSS for Windows Step by Step Darren George, Paul Mallery, 2010 SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 Update makes data analysis and SPSS procedures clear and accessible by presenting straightforward “step by step” instructions in each analysis chapter to clarify procedures. Exercises at the end of each chapter and selected answers on the website give students an opportunity to practice using SPSS. Updated to reflect SPSS Version 17.0 . |
| spss 17.0 guide to data analysis: Quantitative Analysis and IBM® SPSS® Statistics Abdulkader Aljandali, 2016-11-08 This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, GSK, TfL, the NHS, Shell, Unilever, and W.H.S. Although the emphasis in this guide is on applications of IBM SPSS Statistics, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the package; therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum. |
| spss 17.0 guide to data analysis: Applied Longitudinal Data Analysis for Epidemiology Jos W. R. Twisk, 2013-05-09 This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies. |
| spss 17.0 guide to data analysis: Statistical Analysis Quick Reference Guidebook Alan C. Elliott, Wayne A. Woodward, 2007 A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes. |
| spss 17.0 guide to data analysis: Interpreting Quantitative Data with IBM SPSS Statistics Rachad Antonius, 2012-11-21 The second edition of Interpreting Quantitative Data with IBM SPSS Statistics is an invaluable resource for students analysing quantitative data for the first time. The book clearly sets out a range of statistical techniques and their common applications, explaining their logic and links to the research process. It also shows how SPSS can be used as a tool to aid analysis. Key features of the second edition include: - new chapters on one-way and two-way ANOVA, the Chi-square test and linear regression. - SPSS lab sessions following each chapter which demonstrate how SPSS can be used in practice - sets of exercises and ′real-life′ examples to aid teaching and learning - lists of key terms to aid revision and further reading to enhance students′ understanding - an improved text design making the book easier to navigate - a companion website with answers to the labs and exercises, along with additional data sets and powerpoint slides |
| spss 17.0 guide to data analysis: A Visual Approach to SPPS [sic] for Windows Leonard D. Stern, 2008 SPSS is, essentially, a visually-driven program, but most texts rely primarily on a verbal approach to describe its use. A Visual Approach to SPSS for Windows is the first text of its kind to employ what the author refers to as visual sequencing to teach student how to use SPSS. |
| spss 17.0 guide to data analysis: An Introduction to Categorical Data Analysis Alan Agresti, 2018-11-20 A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences. |
| spss 17.0 guide to data analysis: Biostatistics Wayne W. Daniel, Chad L. Cross, 2018-11-13 The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference. |
| spss 17.0 guide to data analysis: Data Analysis Using SQL and Excel Gordon S. Linoff, 2010-09-16 Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like. |
| spss 17.0 guide to data analysis: SPSS for Windows Step by Step Darren George, Paul Mallery, 2003 This text covers all major SPSS procedures for version 11.0 and earlier versions. Each analysis chapter is organized according to a structured, identical format, with step-by-step instructions. |
| spss 17.0 guide to data analysis: Amos 17.0 User's Guide James Arbuckle, 2008-01-01 |
| spss 17.0 guide to data analysis: Statistics in a Nutshell Sarah Boslaugh, 2012-11-15 A clear and concise introduction and reference for anyone new to the subject of statistics. |
| spss 17.0 guide to data analysis: An Introduction to Statistics and Data Analysis Using Stata® Lisa Daniels, Nicholas Minot, 2025-01-10 An Introduction to Statistics and Data Analysis Using Stata®: From Research Design to Final Report, Second Edition provides an integrated approach to research methods, statistics and data analysis, and interpretation of results in Stata. Drawing on their combined 25 years of experience teaching statistics and research methods, authors Lisa Daniels and Nicholas Minot frame data analysis within the research process—identifying gaps in the literature, examining the theory, developing research questions, designing a questionnaire or using secondary data, analyzing the data, and writing a research paper—so readers better understand the context of data analysis. Throughout, the text focuses on documenting and communicating results so students can produce a finished report or article by the end of their courses. The Second Edition has been thoroughly updated with all new articles and data—including coverage of ChatGPT, COVID-19 policies, and SAT scores—to demonstrate the relevance of data analysis for students. A new chapter on advanced methods in regression analysis allows instructors to better feature these important techniques. Stata code has been updated to the latest version, and new exercises throughout offer more chances for practice. |
| spss 17.0 guide to data analysis: Discrete Data Analysis with R Michael Friendly, David Meyer, 2015-12-16 An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth |
| spss 17.0 guide to data analysis: PISA PISA Data Analysis Manual: SPSS, Second Edition , 2009-04-21 Rev. ed. of: PISA 2003 data analysis manual. SPSS users. c2005. |
| spss 17.0 guide to data analysis: IBM SPSS Statistics 23 Step by Step Darren George, Paul Mallery, 2016-03-22 IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference, 14e, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of vivid, four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. All datasets used in the book are available for download at: https://www.routledge.com/products/ 9780134320250 |
| spss 17.0 guide to data analysis: Statistical Methods in Water Resources D.R. Helsel, R.M. Hirsch, 1993-03-03 Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences. |
| spss 17.0 guide to data analysis: Ebook: SPSS Surival Manual: A Step by Step Guide to Data Analysis using IBM SPSS Julie Pallant, 2020-04-01 The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant takes you through the entire research process, helping you choose the right data analysis technique for your project. This edition has been updated to include up to SPSS version 26. 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 data output and an example of how to present the results in a report. For both beginners and experienced users in Psychology, Sociology, Health Sciences, Medicine, Education, Business and related disciplines, the SPSS Survival Manual is an essential text. It is illustrated throughout with screen grabs, examples of output and tips, and is also further supported by a website with sample data and guidelines on report writing. This seventh edition is fully revised and updated to accommodate changes to IBM SPSS procedures. |
| spss 17.0 guide to data analysis: Applied Predictive Modeling Max Kuhn, Kjell Johnson, 2013-05-17 Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. |
| spss 17.0 guide to data analysis: Structural Equation Modeling With AMOS Barbara M. Byrne, 2001-04 This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and appli. |
| spss 17.0 guide to data analysis: Introductory Statistics 2e Barbara Illowsky, Susan Dean, 2023-12-13 Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
| spss 17.0 guide to data analysis: PISA Data Analysis Manual: SPSS, Second Edition OECD, 2009-03-31 This publication includes detailed information on how to analyse the PISA data, enabling researchers to both reproduce the initial results and to undertake further analyses. |
| spss 17.0 guide to data analysis: Statistical Methods for Psychology David C. Howell, 2013 STATISTICAL METHODS FOR PSYCHOLOGY, 8E, International Edition surveys the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasizes conceptual understanding. This Eighth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. New and expanded topics—reflecting the evolving realm of statistical methods—include effect size, meta-analysis, and treatment of missing data. |
| spss 17.0 guide to data analysis: Statistical Analysis of Designed Experiments Helge Toutenburg, Shalabh, 2006-05-09 Unique in commencing with relatively simple statistical concepts and ideas found in most introductory statistical textbooks, this book goes on to cover more material useful for undergraduates and graduate in statistics and biostatistics. |
| spss 17.0 guide to data analysis: Illustrating Statistical Procedures: Finding Meaning in Quantitative Data Ray W. Cooksey, 2020-05-14 This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis. |
| spss 17.0 guide to data analysis: Essential First Steps to Data Analysis Carol S. Parke, 2013 The purpose of this book is to provide instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Preparation may involve data management and manipulation tasks, data organization, structural changes to data files, or conducting preliminary analysis such as examining the scale of a variable, the validity of assumptions or the nature and extent of missing data. The oresultso from these essential first steps can also help guide a researcher in selecting the most appropriate statistical tests for his/her study. The book is intended to serve as a supplemental text in statistics or research courses offered in graduate programs in education, counseling, school psychology, behavioral sciences, and social sciences as well as undergraduate programs that contain a heavy emphasis on statistics. The content and issues covered are also beneficial for faculty and researchers who are knowledgeable about research design and able to use a statistical software package, but are unsure of the first steps to take with their data. Increasingly, faculty are forming partnerships with schools, clinics, and other institutions to help them analyze data in their extensive databases. This book can serve as a reference for helping them get existing data files in an appropriate form to run statistical analysis. This book is not a replacement for a statistics textbook. It assumes that readers have some knowledge of basic statistical concepts and use of statistical software, or that they will be learning these concepts and skills concurrently throughout the course. SPSS was chosen to illustrate the preparation, evaluation, and manipulation of data. However, students or researchers who do not use SPSS will benefit from the content since the overall structure and pedagogical approach of the book focuses heavily on the data issues and decisions to be made. |
| spss 17.0 guide to data analysis: Introduction to Statistical Quality Control Douglas C. Montgomery, 2019-11-06 Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines. Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences. A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge. |
| spss 17.0 guide to data analysis: Key Methods in Geography Nicholas Clifford, Gill Valentine, 2010-05-30 Its range is far broader than the majority of methods texts, being concerned with both human and physical geography... Given the seriousness with which Key Methods in Geography approaches all aspects of research, it will continue to find wide favour among undergraduate geographers. - Times Higher Education Textbook Guide All geographers, whatever their interest, need to do research. This book will help them get started in the best possible way, with thoughtful advice on everything from project design, through choice of methods, to data analysis and presentation. The editors have assembled an impressive array of authors, all experts in their chosen field. - Tim Burt, University of Durham Excellent book. Valuable teaching aid. Well written and covers a wide range of methods thoroughly. - Sue Rodway-Dyer, Exeter University This is an excellent book and deals with a number of topics (which I teach) outside of the tutorial module where it is a recommended text for geographers. A very useful textbook throughout a 3 year Geography programme. - Ian Harris, Bangor University Key Methods in Geography is an introduction to the principal methodological issues involved in the collection, analysis and presentation of geographical information. It is unique in the reference literature for providing an overview of qualitative and quantitative methods for human and physical geography. An accessible primer, it will be used by students as a reference throughout their degree, on all issues from research design to presentation. This second edition has been fully revised and updated and includes new chapters on internet mediated research, diaries as a research method, making observations and measurements in the field, and the analysis of natural systems. Organized into four sections: Getting Started in Geographical Research; Generating and Working with Data in Human Geography; Generating and Working with Data in Physical Geography; Representing and Interpreting Geographical Data; each chapter comprises: A short definition A summary of the principal arguments A substantive 5,000-word discussion Use of real-life examples Annotated notes for further reading. The teaching of research methods is integral to all geography courses: Key Methods in Geography, 2nd Edition explains all of the key methods with which geography undergraduates must be conversant. |
| spss 17.0 guide to data analysis: SPSS Introductory Guide Marija J. Norušis, 1982 Blue mondays: data entry and tabulation; Telling the whole truth and nothing but: descriptive statistics; Lost letters in cities and towns: crosstabulation and measures of association; Breaking down discrimination: describing subpopulation differences; Selling canary crunch to junior: testing hypotheses about differences in means; Shirts and beards: correlation and scattergrams; What's your proof? one-way analysis of variance; Beauty and the write: analysis of variance; Fats and rats: distribution-free or nonparametric tests; Statistical models for salary: multiple linear regression analysis; Saving the banks: SPSS command summary. |
| spss 17.0 guide to data analysis: Data Mining with Rattle and R Graham Williams, 2011-02-25 Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings. |
| spss 17.0 guide to data analysis: Dictionary of Statistics & Methodology W. Paul Vogt, R. Burke Johnson, 2011-03-08 In this newly updated Fourth Edition, new terms are defined, new synonyms are included, and both are illustrated with new graphics. Growth in the fields of statistics and methodology has mandated these inclusions. The number of definitions and illustrations has grown from about 2,400 in the third edition to about 2,800 in this one, an increase of around 16 percent. While some entries have been shortened and obsolete ones have been deleted, which helped make room for the new entries, comparatively few terms from the earlier editions have been deleted. The importance of classic terms persists even as new techniques and the terms describing them are invented. Finally, the suggestions for further reading have been updated and a new section on Useful Websites on Statistics and Methodology has been added. |
| spss 17.0 guide to data analysis: Modern Multivariate Statistical Techniques Alan J. Izenman, 2013-03-11 This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before. |
spss怎么下载呀，应该下载哪个版本的呀？？ - 知乎
下载spss的地方很多，大抵有以下几个。 一、spss官网（蛮贵的，个人买不太合算，土豪除外；有的学校和单位会买） 二、经管之家（老的名字叫人大经济论坛） 这里很多雷锋会分享免费程序，但需要 …
如何快速掌握 SPSS ？ - 知乎
学习spss的重点并不在软件本身，而是相关的统计学知识，也就是你要学会怎样去分析“输入数据后，软件给你呈现的结果” 好吧，就让我们回到最初的起点，呆呆的跪在统计学面前
用SPSS可以做什么？如何用好SPSS？ - 知乎
spss可以说是统计分析的入门软件了。从 描述性统计分析 ，到多元统计分析，到模型分钟， SPSS 都可以处理。 而且，操作也不难，是通过窗口操作就可以了，不像 Sas 和R，需要编写需要来实现分析 …
小白爱上SPSS - 知乎
你好！欢迎参加《小白爱上spss》课。 前面我们学习过线性相关分析，已知线性相关分析针对的是符合正态性分布的连续型变量，然而在科学研究中，有些数据不符合正态性分布，有些数据也并不连续， …
spssau 和 spss 的区别有哪些？ - 知乎
我们的答案是当然可以了！关于这个问题，不得不提到spss，这是一个国外的统计分析工具，因为出现时间很久了，现在基本上已经形成一种默契，就是以它为一种标准，但实际上，spssau和spss本质上 …
科研常用的SPSS等软件，个人用户如果想购买正版的可以通过什 …
科研常用的spss等软件，个人用户如果想购买正版的可以通过什么途径？ 价格大概是多少？ SPSS只找到IBM和一家代理公司的网站，且都要询价
一文彻底讲透聚类分析（基于SPSS软件实现） - 知乎
我的《spss统计分析精华版课程》经过长时间的精心准备，终于和大家见面了！ 做这套课的初衷就是因为大家非常需要这样一门“针对小白的、零基础的、实战讲解的，聚焦核心统计方法——SPSS精华版 …
SPSS版本是越新越好吗？用哪个版本更好？ - 知乎
《spss统计学基础与实证研究应用精解》张甜 杨维忠著 清华大学出版社. 本书手把手教会使用spss撰写实证研究类论文或开展数据分析 常用统计学原理、实证研究的套路、调查问卷设计、信度分析、效 …
mac如何成功安装spss，谢谢？ - 知乎
IBM SPSS Statistics是一款专业的 数据统计分析软件 ，无论是在学术研究领域，还是商业经营领域，都起着举足轻重的作用。那么IBM SPSS Statistics的mac版本应该如何安装呢。 安装包在哪里下载？ …
SPSS怎样判断两组数据有无显著差异？ - 知乎
在spss中，判断两组数据有无显著差异主要通过t检验来完成。 具体的步骤我之前曾经出过一期视频进行详细讲解—— 在这个案例中要选的是 独立样本T检验 。
spss怎么下载呀，应该下载哪个版本的呀？？ - 知乎
下载spss的地方很多，大抵有以下几个。 一、spss官网（蛮贵的，个人买不太合算，土豪除外；有的学校和单位会买） 二、经管之家（老的名字叫人大经济论坛） 这里很多雷锋会分享免费程 …
如何快速掌握 SPSS ？ - 知乎
学习spss的重点并不在软件本身，而是相关的统计学知识，也就是你要学会怎样去分析“输入数据后，软件给你呈现的结果” 好吧，就让我们回到最初的起点，呆呆的跪在统计学面前
用SPSS可以做什么？如何用好SPSS？ - 知乎
spss可以说是统计分析的入门软件了。从 描述性统计分析 ，到多元统计分析，到模型分钟， SPSS 都可以处理。 而且，操作也不难，是通过窗口操作就可以了，不像 Sas 和R，需要编写 …
小白爱上SPSS - 知乎
你好！欢迎参加《小白爱上spss》课。 前面我们学习过线性相关分析，已知线性相关分析针对的是符合正态性分布的连续型变量，然而在科学研究中，有些数据不符合正态性分布，有些数据也 …
spssau 和 spss 的区别有哪些？ - 知乎
我们的答案是当然可以了！关于这个问题，不得不提到spss，这是一个国外的统计分析工具，因为出现时间很久了，现在基本上已经形成一种默契，就是以它为一种标准，但实际上，spssau …
科研常用的SPSS等软件，个人用户如果想购买正版的可以通过什么 …
科研常用的spss等软件，个人用户如果想购买正版的可以通过什么途径？ 价格大概是多少？ SPSS只找到IBM和一家代理公司的网站，且都要询价
一文彻底讲透聚类分析（基于SPSS软件实现） - 知乎
我的《spss统计分析精华版课程》经过长时间的精心准备，终于和大家见面了！ 做这套课的初衷就是因为大家非常需要这样一门“针对小白的、零基础的、实战讲解的，聚焦核心统计方 …
SPSS版本是越新越好吗？用哪个版本更好？ - 知乎
《spss统计学基础与实证研究应用精解》张甜 杨维忠著 清华大学出版社. 本书手把手教会使用spss撰写实证研究类论文或开展数据分析 常用统计学原理、实证研究的套路、调查问卷设计 …
mac如何成功安装spss，谢谢？ - 知乎
IBM SPSS Statistics是一款专业的 数据统计分析软件 ，无论是在学术研究领域，还是商业经营领域，都起着举足轻重的作用。那么IBM SPSS Statistics的mac版本应该如何安装呢。 安装包在 …
SPSS怎样判断两组数据有无显著差异？ - 知乎
在spss中，判断两组数据有无显著差异主要通过t检验来完成。 具体的步骤我之前曾经出过一期视频进行详细讲解—— 在这个案例中要选的是 独立样本T检验 。
