1. A quality control engineer knows that 10% of the microprocessor chips produced by a machine are defective. Out of a large shipment‚ five chips are chosen at random. What is the probability that none of them is defective? What is the probability that at least one is defective? 2. An automated manufacturing process produces a component with an average width of 7.55 centimeters‚ with a standard deviation of 0.02 centimeter. All components deviating by more than 0.05 centimeter from the mean must
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random. What is the probability that at least one pair of shoes is obtained? 2. At a camera factory‚ an inspector checks 20 cameras and finds that three of them need adjustment before they can be shipped. Another employee carelessly mixes the cameras up so that no one knows which is which. Thus‚ the inspector must recheck the cameras one at a time until he locates all the bad ones. (a) What is the probability that no more than 17 cameras need to be rechecked? (b) What is the probability that exactly 17
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Probability distribution Definition with example: The total set of all the probabilities of a random variable to attain all the possible values. Let me give an example. We toss a coin 3 times and try to find what the probability of obtaining head is? Here the event of getting head is known as the random variable. Now what are the possible values of the random variable‚ i.e. what is the possible number of times that head might occur? It is 0 (head never occurs)‚ 1 (head occurs once out of 2 tosses)
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cutting a deck of cards for $1‚000. What is the probability that the card for the gambler will be the following? a. A face card – there are 12 face cards in a deck of 52 cards. The probability would be 12/52 b. A queen – there are 4 queens in a deck‚ so the probability would be 4/52 c. A Spade - There are 13 cards of each suit so the probability is 13/52 or ¼. d. A jack of spades - There is only 1 jack of spades in a deck‚ so the probability would be 1/52 2. The employees in the textile
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variable X is a weighted average of the possible values that the random variable can take. Unlike the sample mean of a group of observations‚ which gives each observation equal weight‚ the mean of a random variable weights each outcome xi according to its probability‚ pi. The mean also of a random variable provides the long-run average of the variable‚ or the expected average outcome over many observations.The common symbol for the mean (also known as the expected value of X) is ‚ formally defined by Variance
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other education costs. Most children are working to earn money for their families‚ which increases the child labor in the country. A survey of these child laborers reported that 240‚000 children that work are between 5 and 17 years old. Part of the conditional cash transfer programs are aimed at decreasing the child labor and increasing the child education because most students are required to attend school until they are 12 (Lakhani). The life expectancy at birth for
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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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Week Four Discussion 2 1. In your own words‚ describe two main differences between classical and empirical probabilities. The differences between classical and empirical probabilities are that classical assumes that all outcomes are likely to occur‚ while empirical involves actually physically observing and collecting the information. 2. Gather coins you find around your home or in your pocket or purse. You will need an even number of coins (any denomination) between 16 and 30. You do not
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POVERTY AND CONDITIONAL CASH TRANSFERS A Reaction Paper on the Article Written By Randy David Presented by: JOEFREY C. MIRAFUENTES --oOo-- While the article wished to present the acceptability of the Conditional Cash Transfers as an immediate response of the Philippine Government to the beleaguering effects of poverty‚ it also presented another reality that cannot be obscured away from discussing such societal problem‚ and that is the susceptibility of this stimulus program to be exploited
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Case Study - Hamilton County Judges Case (Chapter 4) Commom Pleas Court Q. 1Probibility of Cases Being Appealed and Q. 2 Probability of Q.3 Probability of Judge Reversed Appeal Rank Reversal Rank Fred Cartolano 0.04511 14 0.00395 Thomas Crush 0.03529 4 0.00297 Patrick Dinkelacker 0.03498 3 0.00636 Timothy Hogan 0.03071 2 0.00358 Robert Kraft 0.04047 10 0.00223 William Matthews 0.04019 7 0.00795 William Morrissey 0.03991 6 0.00726 Norbert Nadel 0.04427 13 0.00676 Arthur Ney Jr. 0.03883 5 0.00435
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