SPSS for Applied Sciences


Book Description

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.




Applied Statistics with SPSS


Book Description

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 Using SPSS, STATISTICA and MATLAB


Book Description

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.




Doing Quantitative Research in Education with IBM SPSS Statistics


Book Description

This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.




SPSS Statistics for Data Analysis and Visualization


Book Description

Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.




Applied Multivariate Statistics for the Social Sciences


Book Description

Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.




Basic Statistical Analysis For Applied Sciences


Book Description

The advent of statistical tools is very robust through the statistical software. One of the famous software that is being used by thousands of researchers is SPSS. This book assists the readers to identify the types of analysis needed and clarify the differences between parametric and nonparametric analyses. This will guide the readers to choose the most effective statistical analysis to represent their case study. The simple and attractive, yet comprehensive presentation aims to provide the students, new or advanced researchers with understanding of the basic concept and the right procedure for data analysis. The provided guide will help in formulating good presentations and conclusions based on the results obtained and subsequently providing valuable information on statistical methods in applied research.




Proceedings of the 4th International Conference on Applied Economics and Social Science, ICAESS 2022, 5 October 2022, Batam, Riau Islands, Indonesia


Book Description

This volume contains a collection of papers presented at The 4th International Conference on Applied Economics and Social Science (ICAESS) 2022, which was held on 5th October 2022, In Batam, Indonesia online. Batam is the city of Politeknik Negeri Batam, which organized ICAESS. This conference’s aim is to showcase research applications conducted by researchers. The research gap between academics and industries had become a significant challenge which is expected to be addressed during the conference. Our theme is "Responding the Era of Metaverse for Future Applied Technology". We have keynote speakers that delivering talks for the digital marketplace: Dr Hj Mohammad Nabil Almunawar, metaverse for education: Prof. Yusep Rosmanyah, S.T., M.Sc, PhD, and industry 4.0: Ashwani Singh, PhD. We are indebted to them, we hope their research continues successfully. ICAESS has 4 tracks including Economics Track, Accountings Track, Managements Track, and Social Sciences Track. We received 112 papers addressing topics in line from the tracks, including Economic Development, Accounting Theory, Business Administration, Development Studies and other related fields. We accepted 50 articles, with an acceptance rate of 45%. Special thanks to the Organizing Committee members along with the numerous reviewers for their assistance with the reviews of the submitted manuscripts. Finally, we sincerely express gratitude to all the participants, and the authors for all their work, thus making this conference a success. We also want to thank the staff of EAI for their help in making this publication possible.




R - FOR BASIC AND APPLIED SCIENCES


Book Description

R is a Statistcal programming language. R is Free and open source. R is an interpreted language not a compiled one. The R programming environment contains the range of tools for parallel computing, machine and deep learning and for working with big Data, including Torch and Tensar flow facilitating construction and implementation of neural networks. The Bioconductor repository contains over a thousand of software packages written in R for analyzing data sets from CDNA microarrays to copy-number variation and epigenomics (Robert Gentleman-Sorin Draghicia). Due to Data Handling and Modeling capabilities and its flexibility, R is becoming the most widely used software in bioinformatics. The R program is built from a variety of packages. These packages are libraries of commands. The Packages are available from the CRAN website. The current R is the result of a collaborative effort of the R core Group. R has many functions for statistical analysis and graphics. R has an effective data handling and storage facility. R provides operators for calculation on arrays, vectors, lists and matrices. This Book Covers all these with suitable examples. R has a collection of tools for data analysis. Keeping in view the Beginners apprehensions the Book provides the Salient Features of Descriptive Statistics & Covers the specific R tools for Statistical analysis. Throughout the Book examples are accompanied by R commands for easy reference. This Book Covers data handling, graphics, and a wide range of Statistical techniques. The Book would be of immense help to basic sciences, Engineering, Business Statistics, medicine streams, Biotechnology, Pharma, Bioinformatics, Genetics and Epidemiology.




Applied Analysis of Variance in Behavioral Science


Book Description

A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data. Discussion focuses primarily on univariate data, but multivariate generalizations are to