...Factor Analysis in SPSS To conduct a Factor Analysis, start from the “Analyze” menu. This procedure is intended to reduce the complexity in a set of data, so we choose “Data Reduction” from the menu. And the choice in this category is “Factor,” for factor analysis. This dataset gives children’s scores on subtests of the Wechsler Intelligence Scale for Children (WISC-III). The Wechsler scales are scored to give you a “verbal” and a “performance” IQ. The question is whether we can reproduce the verbal vs. nonverbal distinction, with the appropriate subtests grouping into each category, using factor analysis. This dialog box will appear: Factor analysis has no IVs and DVs, so everything you want to get factors for just goes into the list labeled “variables.” In this case, it’s all the variables. In some datasets, there is also a dummy “subject number” variable included. Be sure that you don’t include subject number as one of the variables for your factor analysis! To do a factor analysis, we need to select an “extraction method” and a “rotation method.” Hit the “Extraction” button to specify your extraction method. In this dialog box, you can make a number of selections. First, I want you to un-check the box labeled “Unrotated factor solution.” This is a default setting for your printout, but it just gives you information that you don’t need, and that may distract you from the real answers. So, always go into the Extraction sub-dialog and un-check this...
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...Chapter 14 Factor analysis 14.1 INTRODUCTION Factor analysis is a method for investigating whether a number of variables of interest Y1 , Y2 , : : :, Yl, are linearly related to a smaller number of unobservable factors F1, F2, : : :, Fk . The fact that the factors are not observable disquali¯es regression and other methods previously examined. We shall see, however, that under certain conditions the hypothesized factor model has certain implications, and these implications in turn can be tested against the observations. Exactly what these conditions and implications are, and how the model can be tested, must be explained with some care. 14.2 AN EXAMPLE Factor analysis is best explained in the context of a simple example. Students entering a certain MBA program must take three required courses in ¯nance, marketing and business policy. Let Y1, Y2 , and Y3 , respectively, represent a student's grades in these courses. The available data consist of the grades of ¯ve students (in a 10-point numerical scale above the passing mark), as shown in Table 14.1. Table 14.1 Student grades Student no. 1 2 3 4 5 Finance, Y1 3 7 10 3 10 Grade in: Marketing, Y2 6 3 9 9 6 Policy, Y3 5 3 8 7 5 °Peter Tryfos, 1997. This version printed: 14-3-2001. c 2 Chapter 14: Factor analysis It has been suggested that these grades are functions of two underlying factors, F1 and F2, tentatively and rather loosely described as quantitative ability and verbal ability, respectively. It is...
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...IV. External Analysis A. General Environment B. Industry and Competitor Analysis C. Summary and Conclusion Critical Success Factors |CSF |Assigned Weight |CSF Importance to the Industry | | | | | |Length of service in the industry |0.10 |Years of experience as a key factor to | | | |success makes an impression which affects | | | |clients' preferences in choosing which | | | |product supplier or service provider has | | | |deeper understanding on such industry. The | | | |more years of experience an enterprise has, | | | |the more credibility it earns. | |Strong online presence |0.05 |It is a factor which calls the attention of | | | |the clients. It also serves as an | | ...
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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 | |N |Mean |Std. Deviation | |The tutorials are useful and |434 |4.09 |.922 | |relevant | | | | |The tutor is well prepared |436 |4.11 |.962 | |The tutor is knowledgeable |432 |4.19 |.807 | |The tutor is approachable |432 |4.31 |.825 | |The tutor is readily available for |434 |3.93 |.989 | |consultation with students | | | | |In this tutorial I feel free to ask|433 |4.26 |.780 | |questions | | | | |The tutor encourages students to |435 |3.77 |.916 | |think for themselves...
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...Regression with Categorical Predictors Using Personality Inventory variables and perform two factor analysis, one using unrotated solution, and another using rotated orthogonal solution. Q1. Are the communalities the same using either method? Factor Analysis 1 – Unrotated Solution Communalities | | Initial | Extraction | Beck's Depression Inventory | 1.000 | .666 | measures the extent to which a person is impulsive the higher the value the more impulsive the person is | 1.000 | .643 | Rotter Locus of Control Measure | 1.000 | .666 | Life Optimism Test | 1.000 | .798 | indicator for whether the South Oaks Gambling Screen suggests that the person is a probable pathological gambler | 1.000 | .654 | Extraction Method: Principal Component Analysis. | Factor Analysis 2 – Rotated Orthogonal Solution Communalities | | Initial | Extraction | Beck's Depression Inventory | 1.000 | .666 | measures the extent to which a person is impulsive the higher the value the more impulsive the person is | 1.000 | .643 | Rotter Locus of Control Measure | 1.000 | .666 | Life Optimism Test | 1.000 | .798 | indicator for whether the South Oaks Gambling Screen suggests that the person is a probable pathological gambler | 1.000 | .654 | Extraction Method: Principal Component Analysis. | Yes; the communalites are the same. Q2: Using unrotated solution, for the first factor, calculate extraction communalities from component matrix. Component Matrixa | |...
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...OF SOUTHEASTERN PHILIPPINES COLLEGE OF GOVERNANCE AND BUSINESS B.O. Obrero, Davao City EXPLORATORY FACTOR ANALYSIS ON GANGSTERISM _________________________ In Partial Fulfilment of the Requirement for the Subject Data Analysis for Administrators _________________________ SHERWIN S. FORTUGALIZA September 2015 A total of two hundred sixty three (263) secondary students of Davao City National High School from different grade levels and programs were chosen as respondents to answer the questionnaire on gangsterism. The total number of respondents satisfied the requirement of 10 is to 1 subject-item ratio of Nunnally (1978). Measures of Sampling Adequacy and Sphericity KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .756 Bartlett's Test of Sphericity Approx. Chi-Square 1191.498 df 190 Sig. .000 Based from the result, A KMO of .756 which is near 1 signifies a pattern for correlations that are relatively compact which provide reliable factors. In general, a KMO coefficient must be greater than 0.50. Literatures indicate that KMO values between 0.5 to 0.7 were mediocre; values between 0.7 to 0.8 were considered good; and values between 0.8 to 0.9 were great; while values above 0.93 were deemed superb, with the latter suggestive of strong confidence that factor analysis fit for the data (Tamayo, 2012). Moreover, Bartletts Test of Sphericity of 1191.498 is significant with a ...
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...10.3.3 The Influence of etching parameter on Etch Factor: In order to obtain the effect of etching parameter on etching performance for each different level, the average response of each fixed parameter & level for each etching performance are summed up. Table no. 10.8 shows the total average response & the level of three parameter on Etch factor . The result shows that the optimum etching performance for the Etch factor is obtain at temp. of 600c, Conc. of 700 gm/lit, Time of 8min. This is the optimum setting obtained under the condition in which the experiments were performed. The Etch factor decreases with increase Concentration. The result of ANOVA for the Etch factor is presented in table 10.9. According to F-test, the 95% confidence...
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...Human Factors Analysis and Classification System Abstract As aircrafts become more reliable over the years, humans have progressively become more of a causal factor in aviation accidents. Thus, being able to analyze an accident from a human factor perspective is of paramount importance. However, a proper framework of accident analysis is necessary to address the complex and often nebulous nature of human error. The Human Factors Analysis and Classification System Maintenance Extension (HFACS-ME) is one such framework that serves as an accident investigation and data analysis tool. This article will analyze how HFACS-ME is used from an applied perspective and demonstrate its utility using case studies. Human Factors Analysis and Classification System Maintenance Extension The Human Factors Analysis & Classification System (HFACS) was originally developed to analyze and classify human errors and other factors contributing to aviation incidents. HFACS combines features from Heinrich’s “Domino Theory” and Edward’s “SHEL Model” as well as Reason’s model to uncover factors that contribute to accidents (Schmidt, J. Lawson, D., n.d.). The Maintenance Extension of HFACS termed HFACE-ME was created to address aviation maintenance related incidents and facilitates the recognition of defective or absent defenses at four levels namely, Unsafe: Management Conditions, Maintainer Conditions, Working Conditions, and Maintainer...
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...Factor Analysis Assignment 1. The principal component analysis is the approach that is used for data reduction and creation of one or more than one index variables from the large number of variables. This happens with the use of linear combination of variables. The index variable that is created from this analysis is called components. While, the Factor Analysis is the approach that is used for data reduction in different way than principal component analysis. It is the measurement model of latent variable. This cannot be measured directly with one variable rather, it is observed through the relationship between x and y variables. 2. The general approach (Kaiser) is to retain factors with eigenvalue ≥ 1 and eliminate factors with eigenvalue...
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...INTERNATIONAL FACTORS OF ENVIRONMENT Public administration operates in a global environment that requires a greater emphasis on cooperation among nations. Globalization has become a catch world for international development endeavors throughout the world. With globalization borders between regions and nations are no longer important. A final component of the general environment is actions of other countries or groups of countries that affect the organization. Governments may act to reserve a portion of their industries for domestic firms, or may subsidize particular types of businesses to make them more competitive in the international market. Some countries may have a culture or undergo a change in leadership that limits the ability of firms to participate in the country's economy. As with the other elements of the macroenvironment, such actions are not directed at any single company, but at many firms. ECONOMIC ASSOCIATIONS. One of the most recent joint efforts by governments to influence business practices was NAFTA. The agreement between the United States, Canada, and Mexico was intended to facilitate free trade between the three countries. The result has been a decrease in trade barriers between them, making it easier to transport resources and outputs across national boundaries. The move has been beneficial to many businesses, and probably to the economies of all three countries. In most economic associations, preference is also given to products from member countries...
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...Strategies for Sustainable Channel Relations in Mobile Telecom Sector The main objective of the study is to provide an accurate role for the company executive in developing channel relations. The constructs identified for developing sustainable relationships were Setting distribution objectives, Channel design, Logistics, Image Building, Inventory management, Channel management, Payment & credit, Promotional assistance, Setting targets, Coverage frequency , Motivating channel members to perform. The sample selected contained distributors from the Mobile telecom sector and company executives/channel managers of leading telecom companies. Factor analysis and Friedman’s test was applied. The findings revealed a correlation in attitude between distributors and the executives. Motivating distributors was rated as the most important strategy by the company. The distributors felt that all channel partners needed to have positive attitude towards the channel while company executives felt that aggression made channel members perform effectively. Such findings will be of use to mobile telecom companies who are new entrants to the Indian market and to existing companies who plan to expand their coverage There are 4 GSM and 2 CDMA players, 4800 distributors (Cellular Operators association of India), having 260 company executives. In case of distributors ,the total sample size 240 distributors from the Mobile telecom sector, out of which 120 were high performing( with Rupees 80-90...
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...Page 1 of 8 ANZMAC 2009 Satisfaction with Services: An Impact-Performance Analysis for Soccer-Fan Satisfaction Judgements Marko Sarstedt*, Ludwig-Maximilians-University Munich, sarstedt@lmu.de Manfred Schwaiger, Ludwig-Maximilians-University Munich schwaiger@lmu.de Christian M. Ringle, University of Hamburg & University of Technology, Sydney, cringle@econ.uni-hamburg.de Siegfried Gudergan, University of Technology Sydney, Siggi.Gudergan@uts.edu.au Abstract Fan satisfaction is with services is a key element to successfully compete in the soccer industry. In this paper we examine the antecedent factors that explain the variations in overall service satisfaction judgements. We draw on service an activities put in place by soccer clubs to illustrate these effects. Based on a literature review, interviews with both soccer fans and an industry expert, we develop a measurement approach for satisfaction which we test subsequently using a large-scale sample among soccer fans. An analysis of the impact-performance implications of antecedent drivers shows that stadium features, team characteristics, and fan-based support for the club and its management are the most important factors that influence overall satisfaction. Keywords: customer service, satisfaction, service experience, service providers ANZMAC 2009 Page 2 of 8 Satisfaction with Services: An Impact-Performance Analysis for Soccer-Fan Satisfaction Judgements Literature review on the relevance of fan satisfaction...
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...American Journal of Applied Sciences, 10 (3): 247-252, 2013 ISSN: 1546-9239 ©2013 Science Publication doi:10.3844/ajassp.2013.247.252 Published Online 10 (3) 2013 (http://www.thescipub.com/ajas.toc) RELATIONSHIP BETWEEN TOTAL QUALITY MANAGEMENT PRACTICES AND CONTRACTORS COMPETITIVENESS 1 Faihan Alotaibi, 1Rushami Zien Yusoff and 2Rabiul Islam School of Business Management, School of Economics, Finance and Banking, College of Business, University Utara Malaysia, 06010, Kedah, Malaysia 2 1 Received 2013-04-05, Revised 2013-04-15; Accepted 2013-04-17 ABSTRACT Total quality management is basically about continuous organizational success through the employment of customer satisfaction and by basing it on the contribution of all the employees constantly working to enhance processes, services and products. The competitiveness concept has been defined in multitude of ways; in the individual firm’s context, industries context and nation’s context. The aim of the study is to identify the relationship between total quality management practices and contractors competitiveness. In order to achieve the study objective in the present study, a survey conducted. Questionnaires distributed to the contractor’s managers in Saudi Arabia. The findings of the study turn out to be true; the study will contribute to both theory and practice. Through the present study, the researcher expects the findings to shed light on the research conducted hierarchical regression to analyse the relationships...
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...science and GSR (Galvanic Skin Response) data. As a result of this study, the authors suggest two models of movie trailers boosting customers’ appreciation desire to make a new movie trailer. Keywords: Movie Trailer Production Approach Model; Statistics; GSR INTRODUCTION O ver the last several years, the authors have been conducting applied research on a Customer Science Approach. In this study, the authors research “Effectiveness of Movie Trailers Boosting Customers’ Appreciation Desire” using statistical science and GSR (Galvanic Skin Response) data. First, shared factors that form the backdrop for the structural elements of movie trailers are identified (picture, story, function, etc.) and a numerical model is used to assess their relative impact. Next, GSR experiments are used as a new way to visualize viewers’ emotional responses and identify key factors that motivate them to see the advertised film. Key factors that affect viewer emotions (including changes in picture brightness, changes in the soundtrack, and sound effects) are then traced via changes in the physical chemistry of the test subjects. The authors then use the information gathered during these tests to formulate two new systematic models for creating movie trailers that will effectively motivate viewers to see the advertised film. The models are applied to the remaking...
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...company. It seeks to focus on factors affecting stress and job satisfaction such as number of work hours, good relations between management and employees, good function of the group and work related to employees’ area of education. Design/methodology/approach – A random sample of 425 employees in the private and public sector and two stage cluster sampling is first used to collect primary data. Factor analysis is used next to identify the responsible factors for the correlation among a large number of qualitative and quantitative variables and their influence on productivity. Logistic regression is used next presenting many useful elements concerning the function of stress, satisfaction and supportive elements on productivity. Findings – As expected, increased stress leads to reduced productivity and increased satisfaction leads to increased productivity. When work begins to overlap with workers’ personal life this implies a negative effect on productivity. Quality work is more related to conscientiousness and personal satisfaction than work load. Energetic and active individuals affect productivity positively. Originality/value – The paper presents a number of qualitative variables as factors representing stress and satisfaction. This is achieved using factor analysis. Next logistic regression offers the odds ratio and the corresponding probability of the effect on productivity after a change in stress and satisfaction. The empirical analysis completes the existing literature...
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