Hutcheson: Dictionary of Quantitative Methods in Management. Sage Publications Principal Components Analysis Introduction Principal Components Analysis (PCA) attempts to analyse the structure in a data set in order to define uncorrelated components that capture the variation in the data. The identification of components is often desirable as it is usually easier to consider a relatively small number of unrelated components which have been derived from the data than a larger group of related variables
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Chapter 1 INTRODUCTION 1.1 Background of the Study Since the launching of the Internet in 1960s‚ the continued growth of Internet technology and applications has become an important part of the reality of many people’s lives globally. It provides an ease to the people who are using it. It is used in groups for discussion‚ all of which can be used for social‚ informational‚ educational‚ and even self-help purposes. Internet is somehow the source of entertainment. Even chatting‚ instant messaging
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Principal Component Value at Risk: an application to the measurement of the interest rate risk exposure of Jamaican Banks to Government of Jamaica (GOJ) Bonds Mark Tracey1 Financial Stability Department Research & Economic Programming Division Bank of Jamaica Abstract This paper develops an effective value at risk (VaR) methodology to complement existing Bank of Jamaica financial stability assessment tools. This methodology employs principal component analysis and key rate durations for
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INDEPENDENT COMPONENT ANALYSIS A Tutorial Introduction James V. Stone Independent Component Analysis Independent Component Analysis A Tutorial Introduction James V. Stone A Bradford Book The MIT Press Cambridge‚ Massachusetts London‚ England © 2004 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying‚ recording‚ or information storage and retrieval) without permission
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C8057 (Research Methods II): Factor Analysis on SPSS Factor Analysis Using SPSS The theory of factor analysis was described in your lecture‚ or read Field (2005) Chapter 15. Example Factor analysis is frequently used to develop questionnaires: after all if you want to measure an ability or trait‚ you need to ensure that the questions asked relate to the construct that you intend to measure. I have noticed that a lot of students become very stressed about SPSS. Therefore I wanted to design
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report Preliminary analysis Since the data of all variables are non-metric and ordinal‚ there is no appropriate preliminary analysis can be performed. The descriptive statistics of the variable (table 1) below show that most respondent’s answers falls between 3 to 4 and close to 4 which denote the perception of neutral to agree. That is‚ most answers are positive indicating the students are not on average dissatisfy with the teaching of the subject. Figure 1 |
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to be used in this study is almost research employing a combination of qualitative and quantitive approaches. Problems definition Quantitive research Research design Qualitative research Questionnaire online survey Sampling Fieldwork Data analysis Managerial implications Figure : the stages of customers evaluation research Normally the starting point of any research process is the research problem and research objectives. The next stage is to design plans of getting information
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Fast and Robust Fixed-Point Algorithms for Independent Component Analysis Aapo Hyvärinen Helsinki University of Technology Laboratory of Computer and Information Science P.O. Box 5400‚ FIN-02015 HUT‚ Finland Email: aapo.hyvarinen@@hut.fi IEEE Trans. on Neural Networks‚ 10(3):626-634‚ 1999. Abstract Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible
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FACTOR ANALYSIS Factor analysis is a general name denoting a class of procedures primarily used for data reduction and summarization. It is used in the following circumstances: • To identify underlying dimensions or factors‚ that explains the correlations among the set of variables. • To identify new‚ smaller set of uncorrelated variables to replace the original set of correlated variables in subsequent multivariate analysis. • To identify smaller set of salient variables from a larger set for
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Eleven Multivariate Analysis Techniques: Key Tools In Your Marketing Research Survival Kit by Michael Richarme Situation 1: A harried executive walks into your office with a stack of printouts. She says‚ “You’re the marketing research whiz—tell me how many of this new red widget we are going to sell next year. Oh‚ yeah‚ we don’t know what price we can get for it either.” Situation 2: Another harried executive (they all seem to be that way) calls you into his office and shows you three proposed
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