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Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text′s self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers : 1. A self-study guide for learning how to use SPSS. 2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results. 3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book. Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.
Assuming no previous statistics education, this practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examples using real data, and includes a CD-ROM with software tools and data sets used in the examples and exercises. Readers learn which software tools to apply and also gain insights into the comparative capabilities of the primary software packages.
What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp′s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics.
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
This book offers a quick and basic guide to using SPSS and provides a general approach to solving problems using statistical tests. It is both comprehensive in terms of the tests covered and the applied settings it refers to, and yet is short and easy to understand. Whether you are a beginner or an intermediate level test user, this book will help you to analyse different types of data in applied settings. It will also give you the confidence to use other statistical software and to extend your expertise to more specific scientific settings as required. The author does not use mathematical formulae and leaves out arcane statistical concepts. Instead, he provides a very practical, easy and speedy introduction to data analysis, offering examples from a range of scenarios from applied science, handling both continuous and rough-hewn data sets. Examples are given from agriculture, arboriculture, biology, computer science, ecology, engineering, farming and farm management, hydrology, medicine, ophthalmology, pharmacology, physiotherapy, spectroscopy, sports science, audiology and epidemiology.
Accompanying CD-ROM contains data disk to accompany the text.
Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text′s self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers : 1. A self-study guide for learning how to use SPSS. 2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results. 3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book. Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.
Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available.
This text is designed to teach students how to explore data in a systematic manner using the most popular professional statistics program for social scientists on the market today, SPSS. The book is organised to guide students through the logic of data analysis, from exploring data sets all the way through multivariate analysis and the writing of a research report. *Provides a hands-on approach to teaching statistics. *Focuses on applying statistical measures to understanding social behaviour, rather than on the process of calculating these statistics. *Utilizes a research project approach. *Features end of chapter guided exercises that help students to develop the skills of data analysis in an incremental fashion.