Introduction In-Process Technology was set up in 1985 to produce and sell a thermal oxidation process that could be used to reduce industrial pollution. For years, however, the company performed dismally. In 1992, the current CEO was hired to turn things around, and the company was reorganized and renamed Thermatrix. Eventually, Thermatrix was able to attract good employees using stock options and other competitive compensation and currently has 60 employees and annual sales of approximately $15
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Operational Risk measurement This is defined as “the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This includes legal risk, but excludes strategic and reputation risk”.9 Such risks are likely to be significant in Islamic Banks due to specific contractual features and the general legal environment. Specific aspects that could raise operational risks in Islamic banks include the following: (1) The cancellation risks
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Homework Assignment One Solutions Probability and Probability Distributions 1. A two-sided coin is flipped twice. Calculate the probability of: a. A head on the first flip (1 point) P(H) = [pic]= 0.5 b. A tail on the second flip given that the first flip was a head (1 point) P(T | H) = P(T) = [pic]= 0.5 c. A tail on the first flip and a head on the second flip (1 point) P(TH) = P(T) ( P(H) = (0.5)(0.5) = 0.25 d. At least one head on the two
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with the advertised weight around 50oz. We assumed the series of data containing the classes’ weights to be approximately normal. Since n=48, the large-sample test for population mean was used to determine the plausibility that the advertised weight was true. 2. Color Distribution Analysis The color distribution analysis calculated whether or not the color distribution of the bag of M&Ms accurately depicts the advertised proportions. The number of orange M&Ms in our bag suggested that
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deviation Standard deviation Variance Coeff of variation Inferential Statistics Populations Sampling Estimation of Parameters Point Estimation Interval Estimation Unbiased Minimum Variance Consistency Efficiency Properties of Point Estimators Statistical Inference: Hypothesis Testing T test F test Chi square test Measures of shape of the curve Moments Skewness kurtosis Probability distributions Normal Distribution T-student
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valuable suggestions as well as for ın, help with the interest rate database. Of course, the usual caveat applies. Address for correspondence: Alcal´ 48, E-28014 Madrid, Spain, tel: +34 91 338 5414, fax: +34 91 338 6102. a ∗ 1 Introduction Standard capital market theory states that there is a risk-return tradeoff in equilib- rium. The more risk one is willing to take, the higher the return one will be able to get. This relationship has been extensively analysed in the context of liquid assets
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AVU-PARTNER INSTITUTION MODULE DEVELOPMENT TEMPLATE PROBABILITY AND STATISTICS Draft By Paul Chege Version 19.0, 23rd March, 2007 C. TEMPLATE STRUCTURE I. INTRODUCTION 1. TITLE OF MODULE Probability and Statistics 2. PREREQUISITE COURSES OR KNOWLEDGE Secondary school statistics and probability. 3. TIME The total time for this module is 120 study hours. 4. MATERIAL Students should have access to the core
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ACST828 LECTURE 6 Part 1: Normal distribution: X ~ N , 2 mean (average) Variance 2 probability density function 1 x 2 1 exp f x 2 2 cumulative density function 1 t 2 1 F x dt exp 2 2 Standard Normal Density X ~ N 0,1 probability density function n x cumulative density function x N x 1 1 exp x 2 2 2 x
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discrete variable taking on a particular value, expressed as a percentage These can be estimated by experiments or observations, called empirical probability. Explained in excel Probability Distribution: A Tabulated view of the uncertain behavior of a discrete random variable Cumulative Distribution: Another Tabulated view of the uncertain behavior of a discrete random variable Expectation of a variable: A weighted average taking into account the probability. Difference between DV and
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EDITORIAL Analyzing and Interpreting Data From Likert-Type Scales L ikert-type scales are frequently used in medical education and medical education research. Common uses include end-of-rotation trainee feedback, faculty evaluations of trainees, and assessment of performance after an educational intervention. A sizable percentage of the educational research manuscripts submitted to the Journal of Graduate Medical Education employ a Likert scale for part or all of the outcome assessments
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