Question1: Frequency Distribution. Histograms‚ Cumulative Frequency and Ogives. 1) a) 799 b) 1000 c) 900+9992 = 949.5 d) Lower Class Boundary=1100-0.5 =1099.5 Upper Class Boundary=1199.5+0.5=1199.5 e) 100 f) 76 g) 62400×100=15.5 h) 600-699‚ the fourth class has the largest frequency of 76. i)14+46+58400 ×100=29.5% j) 48+22+6400 ×100=19.0% k) 4002=200 200 lie in the fifth class interval 700-799 ∴The median lies in this interval. =l+n2-cff×h =700+200-19468×99 =708.735 l)
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Vapor deposition modeling for an entrenched wafer geometry L. J. Willett‚ S. K. Loyalka‚ and R. V. Tompson Citation: J. Vac. Sci. Technol. A 17‚ 212 (1999); doi: 10.1116/1.581575 View online: http://dx.doi.org/10.1116/1.581575 View Table of Contents: http://avspublications.org/resource/1/JVTAD6/v17/i1 Published by the AVS: Science & Technology of Materials‚ Interfaces‚ and Processing Related Articles Investigation of arsenic and antimony capping layers‚ and half cycle reactions during atomic layer
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LEAD 6341 Research Methods and Statistics Midterm Exam Part II: Conceptual Problems (Open Book) Spring‚ 2013 1) Very briefly discuss the history of ethical problems in research in the US. Describe how current research policies and practices reduce the likelihood of ethical problems arising from research today. The Tuskegee study is an example of ethical problem in research in the US. The black subjects were promised medical care‚ meals‚ and burial insurance for their participation in
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QM PROJECT QUANTITATIVE METHODS – I PROJECT : ANALYSIS OF AUTO TRAFFIC TO IIMKOZHIKODE CAMPUS GROUP : 26 1. 2. 3. 4. 5. 6. MONISHA MEHROTRA USHA BHAKUNI PARTH LIMBACHIYA TARA RAJAGOPALAN M.ROHIT SULAGNA DATTA - 26 - 57 - 89 - 120 - 151 - 183 Page 1 GROUP 26 QM PROJECT INTRODUCTION : This project was undertaken to document and analyze the number of autos entering the IIM Kozhikode campus. We felt it was important to undertake this project because‚ it’s a very pertinent and relevant
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TOMAS CLAUDIO MEMORIAL COLLEGE Higher Education Pioneer in Eastern Rizal Taghangin‚ Morong‚ Rizal‚ Phillippines * Tel. No: 691-5532/691-5834 Telefax: 691-5595 COLLEGE OF EDUCATION TITLE: GRADING SYSTEM NORM-REFERENCED GRADING PRESENTER:
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Mathematics of Data Management: Content and Reporting Targets Mathematical Processes across all strands: Problem Solving‚ Reasoning and Proving‚ Reflecting‚ Selecting Tools and Computational Strategies‚ Connecting‚ Representing‚ and Communicating. Unit 1 Unit 2 Unit 3 Unit 4 Unit 5 Counting and Probability Introducing probability vocabulary and notation in contexts involving simple counting Counting permutations and combinations Using mathematical notation to describe the
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operation of the equipment in strict accordance with the standards‚ avoid any unnecessary trouble. 1‚ China sand dryer installed equipment shall be not less than 4 hours of empty machine commissioning‚ to ensure the normal operation.In the commissioning process occurs in a city is not the normal situation should be handled in time. 2‚ after the test run quartz sand dryer‚ check and tighten all bolts again‚ check and lack of lubricating oil‚ to load test after test run normally. 3‚ preheating of hot
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Investigating the effect of intraspecific competition on the growth of mung beans Introduction When plants reproduce‚ size is highly correlated with reproductive. The struggle for reproductive survival among plants is the struggle to grow in the face of competition from neighbours. So the question this experiment asks is how competition affects the growth of plants. A plant growing in a nutrient-abundant environment free from competition will exhibit maximum growth. One way to address this question
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Monte Carlo Simulation Risk analysis is part of every decision we make. We are constantly faced with uncertainty‚ ambiguity‚ and variability. And even though we have unprecedented access to information‚ we can’t accurately predict the future. Monte Carlo simulation (also known as the Monte Carlo Method) lets you see all the possible outcomes of your decisions and assess the impact of risk‚ allowing for better decision making under uncertainty What is Monte Carlo simulation? Monte Carlo simulation
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in this interval… if the sample mean or proportion is in the confidence interval the null hypothesis could be inferred. Else‚ the alternative hypothesis would. • What is the predictable distribution for proportions? Why? “Proportions follow a normal distribution provided: n·p ≥ 5 and n·(1– p) ≥ 5 ( Rule of 5 ) Thus the test statistic that we use is: • Can 1000 people represent 2 million? Why? Yes‚ depends how confident you want to be… to be +or- 1% (95% confident) •If Ho: μ ≤
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