HOLIDAY Road tripping with family is supposed to be fun and exciting. It gives me an opportunity to jump in the car and explore somewhere or something that I have never experienced. My 2010 trip to Lampung was both nerve wrecking and exciting at the same time because I got to be in certain situations that I have never been in before. I remember the first time I went to Lampung‚ my family and I were in rush hour traffic. My heart was thumping in my chest so fast because I have never seen traffic
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University of Perpetual Help System Dalta Molino Campus Molino III‚ Bacoor City Probability and Statistics LAGERA‚ Einar John A. Table of Contents Simple Correlation Analysis ................................................................................................. 1 Introduction .................................................................................................................................................................. 1 What is Correlation? ...........
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uniformly distributed over (0‚ 10)‚ calculate the probability that a. X < 3 (Ans: 3/10) b. X > 6 (Ans: 4/10) c. 3 < X < 8. (Ans: 5/10) 2. Buses arrive at a specified stop at 15-minute intervals starting at 7 AM. That is‚ they arrive at 7‚ 7:15‚ 7:30‚ 7:45‚ and so on. If a passenger arrives at the stop at a time that is uniformly distributed between 7 and 7:30‚ find the probability that he waits d. Less than 5 minutes for a
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standard deck of cards drawing a second ace from a standard deck of cards‚ without replacing the first f) drawing an ace from a standard deck of cards drawing a second ace from a standard deck of cards‚ after replacing the first 2. What is the probability of drawing each of the following from a standard deck of cards‚ assuming that the first card is not replaced? a) an ace followed by a 2 b) two aces c) a black jack followed by a 3 d) a face card followed by a black 7 3. Repeat each part of
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I. Probability Theory * A branch of mathematics concerned with the analysis of random phenomena. The outcome of a random event cannot be determined before it occurs‚ but it may be any one of several possible outcomes. The actual outcome is considered to be determined by chance. * The word probability has several meanings in ordinary conversation. Two of these are particularly important for the development and applications of the mathematical theory of probability. One is the interpretation
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Probability theory Probability: A numerical measure of the chance that an event will occur. Experiment: A process that generates well defined outcomes. Sample space: The set of all experimental outcomes. Sample point: An element of the sample space. A sample point represents an experimental outcome. Tree diagram: A graphical representation that helps in visualizing a multiple step experiment. Classical method: A method of assigning probabilities that is appropriate when all the experimental
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PROBABILITY and MENDELIAN GENETICS LAB Hypothesis: If we toss the coin(s) for many times‚ then we will have more chances to reach the prediction that we expect based on the principle of probability. Results: As for part 1: probability of the occurrence of a single event‚ the deviation of heads and tails of 20 tosses is zero‚ which means that the possibility of heads and tails is ten to ten‚ which means equally chances. The deviation of heads and tails of 30 tosses is 4‚ which means that the
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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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P(S) The symbol for the probability of success P(F) The symbol for the probability of failure p The numerical probability of a success q The numerical probability of a failure P(S) = p and P(F) = 1 - p = q n The number of trials X The number of successes The probability of a success in a binomial experiment can be computed with the following formula. Binomial Probability Formula In a binomial experiment
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Conditional Probability How to handle Dependent Events Life is full of random events! You need to get a "feel" for them to be a smart and successful person. Independent Events Events can be "Independent"‚ meaning each event is not affected by any other events. Example: Tossing a coin. Each toss of a coin is a perfect isolated thing. What it did in the past will not affect the current toss. The chance is simply 1-in-2‚ or 50%‚ just like ANY toss of the coin. So each toss is an Independent
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