1. Chi-square Goodness-of-fit Tests Jake is trying to invest his money in stock market‚ is not sure that he could earn a profit or lose his money when he invests to an AT&T company’s stock or a stock market index‚ Dow Jones Industry Average. So he called his friend who works at financial consulting company and heard that the monthly positive and negative investment returns on AT&T and Dow Jones Industry Average were historically almost the same. However the economic situation recently has been getting
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3. FMECA Methodology 3.1 Failure mode effect & criticality analysis FMEA is called as FMECA (failure mode‚ effects and criticality analysis) when it is used for criticality analysis. In general‚ FMECA is performed in two parts: (I) to identify the different failure modes and its effects by failure mode and effect analysis (FMEA); (ii) to Classify failure mode criticality analysis by probability of occurrence and its severity. (Bowles & Pelaez‚ 1995). FMEA is traditionally calculated by developing
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The linkage between Environmental Management Systems implementation and Firms’ economic performance: an Empirical Analysis The summary version Author: K. Nishitani Student: Dang Tien Loc SUBMITTED TO UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM THE NETHERLAND PROGRAMME 1. Paper’s objective the purpose of this paper is to answer the question whether EMS implementation can improves a firm’s performance or not by using panel data from Japanese manufacturing firms during 1996-2007
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L={116*(Y/Yn) for (Y/Yn)>0.008856 903.3*(Y/Yn); Otherwise a = 500*(f(X/Xn –f(Y-Yn)) b = 200*(f(X/Xn –f(Z-Zn)) where Xn ‚Yn and Zn are the tristimulus values of the reference white. A median filter is applied on the L band in order to preserve edges and to reduce noise . A Contrast Limited Adaptive Histogram Equalization (CLAHE) technique is used. To enhance the contrast and the separability between exudates and the background ‚ a Contrast Limited Adaptive
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Univariate Time Series Models (M.Sc. Finance - Exercise 4) Walter Distaso Imperial College Business School w.distaso@imperial.ac.uk Question 1 Consider the following three models that a researcher suggests might be reasonable models of stock market prices. yt yt yt = yt−1 + ut = 0.5yt−1 + ut = 0.8yt−1 + ut (a) What classes of models are these examples of? (b) What would the autocorrelation function for each of these processes look like? (not exactly‚ just the shape) (c) Which model is
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squared elements in the GLCM and it is by default one for constant image. E=∑_(i‚j)▒(i‚j)^2 (3.8) 3.1.2.1.2 Tamura Texture Feature According to quantitative analysis one of the first descriptions given by the Tamura [69] proposed six textural properties and gave descriptions common over all texture patterns in Broadtz’s photographic images. These are six different texture features given by Tamura Coarseness
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Crusty Pizza Restaurant: Forecasting using Regressions Group One: Jenna Baseler and Zachary Kain MBA 610-T304 Introduction The purpose of this case is to determine which key variables drive Crusty Pizza Restaurant’s monthly profit and then forecast what the monthly profit would be for potential stores. Based off of this information we will be able to make a recommendation to Crusty Dough Pizza Restaurant on which stores they should open and which they avoid. The group was provided 60 restaurants’
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A study on the Urban Cooperative Banks Success and growth – Statistical Analysis MR VIVEK KUMAR TIWARI ASSISTANT PROFESSOR CAREER GIRLS DEGREE COLLEGE LUCKNOW UP; Abstract - Urban co-operative banks ranked a very significant position in the Indian banking sector. Competent management is prerequisite for the success of any organization. At present highly competitive and globalized business environment‚ there is an urgent need of professional management for the successful controlling and managing
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course mainly tells us the skill how to collect and collate information and the methods how to do with quantitative analysis and comprehensive evaluation. Specific content include: statistical design‚ statistical research‚ aggregate indexes‚ relative indexes‚ average indexes‚ sign variability indexes‚ time series prediction‚ statistics indexes‚ sample inferred‚ correlation analysis‚ aggregate indexes for the national economy etc. 2. Proportion of Course Hours Chapter Proportion Chapter1 General
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MULTICOLLINEARITY One problem that can arise in multiple regression analysis is multicollinearity. Multicollinearity is when two or more of the independent variables of a multiple regression model are highly correlated. Technically‚ if two of the independent variables are correlated‚ we have collinearity; when three or more independent variables are correlated‚ we have multicollinearity. However‚ the two terms are frequently used interchangeably. The reality of business research is that most of
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