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Master data management & analysis techniques with IBM SPSS Statistics 24 About This Book Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data Choose the right statistical technique to analyze different types of data and build efficient models from your data with ease Overcome any hurdle that you might come across while learning the different SPSS Statistics concepts with clear instructions, tips and tricks Who This Book Is For This book is designed for analysts and researchers who need to work with data to discover meaningful patterns but do not have the time (or inclination) to become programmers. We assume a foundational understanding of statistics such as one would learn in a basic course or two on statistical techniques and methods. What You Will Learn Install and set up SPSS to create a working environment for analytics Techniques for exploring data visually and statistically, assessing data quality and addressing issues related to missing data How to import different kinds of data and work with it Organize data for analytical purposes (create new data elements, sampling, weighting, subsetting, and restructure your data) Discover basic relationships among data elements (bivariate data patterns, differences in means, correlations) Explore multivariate relationships Leverage the offerings to draw accurate insights from your research, and benefit your decision-making In Detail SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with...

Statistics --- Computer programs. --- SPSS (Computer file)

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"The goal of the book is to provide readers with the tools necessary for assessing the psychometric qualities of educational and psychological measures as well as surveys and questionnaires. Each chapter will cover an issue pertinent to psychometric and measurement practice, with an emphasis on application. Topics will be briefly discussed from a theoretical/technical perspective in order to provide the reader with the background necessary to correctly use and interpret the statistical analyses that will be presented subsequently. The anticipated audience for this book includes researchers, practitioners, and graduate students searching for a guide to perform common psychometric analyses on various assessments, as discussed in many psychometric texts. We envision that this text will (a) patiently wait on some office selves begging to be handed to a student as a resource, (b) have a permanent home on desks where it continually rises to the top of the stacks for daily use of the applied researcher, (c) be happily carried in bags to and from work and class by the graduate student learning techniques, (d) be listed proudly as a reference text on syllabi, and finally (e) as an occasional drink coaster while deep thoughts are pondered about how to solve measurement problems. We hope that through such uses, particularly the latter, that we have provided some insight and assistance to the user in appropriately applying the techniques and concepts discussed"--

Educational tests and measurements --- Psychometrics. --- Educational psychology. --- Methodology. --- Mathematical models. --- SPSS (Computer file) --- AMOS.

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'Adventures in Criminal Justice Research' teaches students how to analyse issues and use the computer program SPSS for criminal justice research. The book explains with step by step instructions and over 150 screen shots.

Criminal justice, Administration of --- Information storage and retrieval systems --- Data processing. --- Statistical methods. --- Criminal justice, Administration of. --- SPSS (Computer file). --- Administration of criminal justice --- Justice, Administration of --- Crime --- Criminal law --- Criminals --- Law and legislation --- SPSS (Computer file) --- Statistical package for the social sciences

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Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler About This Book Get up?and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy?to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Who This Book Is For This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book. What You Will Learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions In Detail IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn ?visual programming? style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This bo...

Social sciences --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Statistical methods --- Data processing. --- SPSS (Computer file) --- Statistical package for the social sciences

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Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation, along with a sample size analysis for common time serie

Forecasting. --- Social sciences --- Time-series analysis. --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Forecasts --- Futurology --- Prediction --- Statistical methods. --- SAS (Computer file) --- SPSS (Computer file) --- Statistical package for the social sciences --- Statistical analysis system --- SAS system --- Social prediction --- Time-series analysis --- 519.55 --- #SBIB:002.AANKOOP --- #SBIB:303H4 --- #SBIB:303H520 --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Prediction, Social --- Social forecasting --- Sociological prediction --- Forecasting --- Sociology --- Social indicators --- Computer programs --- Forecasting&delete& --- Statistical methods --- Statistical methods&delete& --- Informatica in de sociale wetenschappen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Programming --- SPSS (statistical package for the social sciences)