Statistical Reasoning in Everyday Life This chapter taught me the importance of understanding statistical data and how to evaluate it with common sense. Almost everyday we are subjected to statistical data in newspapers and on TV. My usual reaction was to accept those statistics as being valid. Which I think is a fair assessment for most people. However‚ reading this chapter opens my eyes to the fact that statistical data can be very misleading. It shows how data can be skewed to support a certain
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-------------------------------------------------------------------------------- 6 BASIC STATISTICAL TOOLS There are lies‚ damn lies‚ and statistics...... (Anon.) -------------------------------------------------------------------------------- 6.1 Introduction 6.2 Definitions 6.3 Basic Statistics 6.4 Statistical tests -------------------------------------------------------------------------------- 6.1 Introduction In the preceding chapters basic elements for the proper
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Non-Hierarchical Cluster Analysis Non-hierarchical cluster analysis (often known as K-means Clustering Method) forms a grouping of a set of units‚ into a pre-determined number of groups‚ using an iterative algorithm that optimizes a chosen criterion. Starting from an initial classification‚ units are transferred from one group to another or swapped with units from other groups‚ until no further improvement can be made to the criterion value. There is no guarantee that the solution thus obtained
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4.5. EXPLORATORY FACTOR ANALYSIS Table 4.14 KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .896 Bartlett’s Test of Sphericity Approx. Chi-Square 4.120E3 df 528 Sig. .000 Bartlett’s test of sphericity indicates whether the correlation matrix is an identity matrix‚ which would indicate that the variables are unrelated. The significance level gives the result of the test. Very small values (less than .05) indicate that there are probably significant relationships
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Multivariate analysis of variance Multivariate analysis of variance (MANOVA) is a generalized form of univariate analysis of variance (ANOVA). It is used when there are two or more dependent variables. It helps to answer : 1. do changes in the independent variable(s) have significant effects on the dependent variables; 2. what are the interactions among the dependent variables and 3. among the independent variables.[1] Where sums of squares appear in univariate analysis of variance‚ in multivariate
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Amanda Mueller MBA6018 – Data Analysis Unit 3 Activity 1 January 23‚ 2013 Practical Application Scenario 1 In 2010‚ Playbill Magazine contracted Boos Allen to conduct a survey aimed at determining the average annual household income of Playbill readers. 300 readers were randomly pulled and sampled from the list of customers provided by Playbill Magazine. From that sampling effort‚ Boos Allen was confident that the population average household income is $119‚155 and that the population
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Research Design Content analysis is a process in which narrative data are divided into units of analysis to examine the contents of a particular body of material for the purpose of identifying patterns‚ themes or biases (Leedy and Ormrod‚ (2005). Further‚ qualitative content analysis has been defined in other ways such as: • “a research method for the subjective interpretation of the content of text or [narrative] data through the systematic classification process of coding and identifying
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The Disadvantages of Using SWOT Analysis by Steven Symes‚ Demand Media SWOT analysis‚ strength‚ weakness‚ opportunities and threats analysis‚ provides a structure for organizations‚ including small businesses‚ to analyze it internally. The analysis examines an organization’s assets‚ processes and past levels of achievement. While SWOT analysis provides some benefits to an organization‚ using it in your small business can put you at a disadvantage unless you understand its limits and risks. Other
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Bivariate analysis Contingency table In this case‚ we use contingency table to analyze the relationship between 2 qualitative variables. And this test works by comparing expected and observed frequencies with x2 distribution. Correlation coefficient When we need to test the relationship between 2 quantitative variables‚ we use correlation coefficient and it measured by standardized covariance measure and investigates linear dependence. Before doing this‚ it is better to first make a scatterplot
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LOAD FLOW ANALYSIS [CONTENTS: Review of solution of equations‚ direct and iterative methods‚ classification of buses‚ importance of slack bus and YBUS based analysis‚ constraints involved‚ load flow equations‚ GS method: algorithms for finding the unknowns‚ concept of acceleration of convergence‚ NR method- algorithms for finding the unknowns‚ tap changing transformers‚ Fast decoupled load flow‚ illustrative examples] REVIEW OF NUMERICAL SOLUTION OF EQUATIONS The numerical analysis involving
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