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Handbook of Univariate and Multivariate Data Analysis with IBM SPSS

Handbook of Univariate and Multivariate Data Analysis with IBM SPSS
Author: Robert Ho
Publisher: CRC Press
Total Pages: 600
Release: 2013-10-25
Genre: Mathematics
ISBN: 1439890226

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Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics


Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS

Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS
Author: Robert Ho
Publisher: CRC Press
Total Pages: 426
Release: 2006-03-24
Genre: Mathematics
ISBN: 1420011111

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Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation. This can leave readers with little understanding of how to apply statistical tests or how to interpret their findings. While the SPSS statistical software has done much to alleviate the frustrations of s


Quantitative Analysis and IBM® SPSS® Statistics

Quantitative Analysis and IBM® SPSS® Statistics
Author: Abdulkader Aljandali
Publisher: Springer
Total Pages: 190
Release: 2016-11-08
Genre: Business & Economics
ISBN: 3319455281

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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.


A Handbook of Statistical Analyses Using SPSS

A Handbook of Statistical Analyses Using SPSS
Author: Sabine Landau
Publisher: Chapman & Hall/CRC
Total Pages: 0
Release: 2017-09-11
Genre: SPSS (Computer file)
ISBN: 9781138462496

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Shows how to conduct a range of univariate and multivariate statistical analysis using the Statistical Package for the Social Sciences, version 11. This title addresses various types of analytical procedure that are applied to data sets, primarily from the social and behavioral sciences areas. It is suitable for researchers in psychology.


Multivariate Methods and Forecasting with IBM® SPSS® Statistics

Multivariate Methods and Forecasting with IBM® SPSS® Statistics
Author: Abdulkader Aljandali
Publisher: Springer
Total Pages: 185
Release: 2017-07-06
Genre: Business & Economics
ISBN: 3319564811

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This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).


SPSS Statistics: A Practical Guide 5e

SPSS Statistics: A Practical Guide 5e
Author: Kellie Bennett
Publisher: Cengage AU
Total Pages: 23
Release:
Genre: Psychology
ISBN: 0170460169

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SPSS Statistics: A Practical Guide gives students step-by-step guidance through the process of using SPSS software to analyse, interpret and report on data. This spiral bound text is concise yet detailed, and is praised for its friendly, practical, and visual pedagogical approach that focuses on ‘doing’. The illustrated step-by-step examples work through each statistical procedure and are followed by interpretation and reporting of results in APA style. Resources for the instructor include Instructor Manual, PowerPoints, practical exercises and datasets, revision quizzes, syntax sets, and more.


Applied Statistics and Multivariate Data Analysis for Business and Economics

Applied Statistics and Multivariate Data Analysis for Business and Economics
Author: Thomas Cleff
Publisher:
Total Pages: 474
Release: 2019
Genre: Big data
ISBN: 9783030177683

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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.


IBM SPSS by Example

IBM SPSS by Example
Author: Alan C. Elliott
Publisher: SAGE Publications
Total Pages: 278
Release: 2014-12-31
Genre: Social Science
ISBN: 1483319040

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The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s "cut to the chase" IBM SPSS guide 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. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.


MULTIVARIATE DATA ANALYSIS

MULTIVARIATE DATA ANALYSIS
Author: R. Shanthi
Publisher: MJP Publisher
Total Pages: 448
Release: 2019-06-10
Genre: Mathematics
ISBN:

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Multivariate Data Analysis Introduction to SPSS Outliers Normality Test of Linearity Data Transformation Bootstrapping Homoscedasticity Introduction to IBM SPSS – AMOS Multivariate Analysis of Variance (MANOVA) One Way Manova in SPSS Multiple Regression Analysis Binary Logistic Regression Factor Analysis Exploratory Factor Analysis Confirmatory Factor Analysis Cluster Analysis K - Mean Cluster Analysis Hierarchical Cluster Analysis Discriminant Analysis Correspondence Analysis Multidimensional Scaling Example - Multidimensional Scaling (ALSCAL) Neural Network Decision Trees Path Analysis Structural Equation Modeling Canonical Correlation