BRAIN CONTROLLED CAR FOR DISABLED USING ARTIFICIAL INTELLIGENCE [pic] Presented by V.DIVYA SRI M.V.LAKSHMI III CSE III CSE EMAIL: vds555@gmail.com EMAIL: morampudi.lakshmi@gmail.com Phone No. 9949422146 Of SHRI VISHNU ENGINEERING COLLEGE
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APPLIED PROBABILITY AND STATISTICS APPLIED PROBABILITY AND STATISTICS DEPARTMENT OF COMPUTER SCIENCE DEPARTMENT OF COMPUTER SCIENCE STATISTICAL DISTRIBUTION STATISTICAL DISTRIBUTION SUBMITTED BY – PREETISH MISHRA (11BCE0386) NUPUR KHANNA (11BCE0254) SUBMITTED BY – PREETISH MISHRA (11BCE0386) NUPUR KHANNA (11BCE0254) SUBMITTED TO – PROFESSOR SUJATHA V. SUBMITTED TO – PROFESSOR SUJATHA V
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[pic] Trial by Fire Did Texas execute an innocent man? by David Grann September 7‚ 2009 [pic] Cameron Todd Willingham in his cell on death row‚ in 1994. He insisted upon his innocence in the deaths of his children and refused an offer to plead guilty in return for a life sentence. Photograph by Ken Light. Related Links Audio: Grann on the Texas execution that may change the death penalty debate. Video: David Grann discusses the flaws of the Cameron Todd Willingham
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God On Trial Christian Worldview Integration Dr. Carl B. Smith II Its impossible to reflect on the origins of evil without bringing up the concept of free will. God created man with this idea of choice; the choice to believe and obey‚ or the choice to disobey. It was this free will that allowed Adam and Eve to fall from their initial glory and introduce evil and suffering into the world. We can justify a large amount of sustained suffering by acknowledging that it actually benefits us and is not
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STAT 110 INTRODUCTION TO DESCRIPTIVE STATISTICS Fall‚ 2006 Lecture Notes Joshua M. Tebbs Department of Statistics The University of South Carolina TABLE OF CONTENTS STAT 110‚ J. TEBBS Contents 1 Where Do Data Come From? 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Individuals‚ variables‚ and data . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Observational studies . . . . . . . . . . . . . . . .
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CHAPTER 1 Individuals are the objects described by a set of data. Individuals may be people‚ but they may also be animals or things. A variable is any change of an individual. A variable can take different values for different individuals. A categorical variable places an individual into one of several groups or categories. A quantitative variable takes numerical values for which arithmetic operations such as adding and averaging make sense. The distribution of a variable tells us what values
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Ratio | Industry benchmark ratio | Woolworths’ ratio | Brief Comment | Current Ratio | 1.2:1 | 0.80:1 | The current ratio ofWoolworth is considerablybelow industry average themovement from it is 33.33% (1.2-0.8)/1.2*100) Which is not really good for business | Liquid ratio | 0.7:1 | 0.34:1 | The Liquid ratio of Woolworth is considerably below industry average. The movement is 51.43 %. It is showed that the business may have problem in paying their debt.(0.7-0.34/0.7*100) | Gross Profit ratio
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1. “What is the life expectancy for Caucasian males that have survived 54 years?” The answer will almost certainly be larger than 72. I want an estimate “conditioned on” the fact that I have already lived 54 years. Life is dynamic. Things are constantly changing. However‚ too often decisions are based on static information. Bayes theorem takes advantage of dynamic information to give a better‚ more correct answer. Bayes Theorem is a mathematical representation that helps one to calculate conditional
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QUESTION 21 The finishing process on new furniture leaves slight blemishes. The table below displays a manager’s probability assessment of the number of blemishes on one piece of new furniture. Number of Blemishes 0 1 2 3 4 5 Probability 0.34 0.25 0.19 0.11 0.07 0.04 1. On average‚ how many blemishes do we expect on one piece of new furniture? 2. What is the variance of blemishes on one piece of new furniture? (round to the nearest hundredth) QUESTION 22 The probability
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EMBA Ranking 2012 Rank 2012 3 year average School name Programme name Salary today (US$) Salary increase (%) Career progress rank Work experience rank Aims achieved rank International course experience rank FT.com Business School Rankings - Custom PDF download 1 1 Kellogg / Hong Kong UST Business School Kellogg-HKUST EMBA 465‚774 42 25 2 1 41 2 2 Columbia / London Business School EMBA-Global Americas and Europe 265‚596
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