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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BBA (Fall - 2014) Business Statistics Theory of Probability Ahmad Jalil Ansari Business Head Enterprise Solution Division Random Process In a random process we know that what outcomes or events could happen; but we do not know which particular outcome or event will happen. For example tossing of coin‚ rolling of dice‚ roulette wheel‚ changes in valuation in shares‚ demand of particular product etc. Probability It is the numeric value representing the chance‚ likelihood‚ or possibility
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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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Study Guide for Probability Multiple Choice Identify the choice that best completes the statement or answers the question. ____ 1. Which inequality represents the probability‚ x‚ of any event happening? a.||c.|| b.||d.|| ____ 2. Which event has a probability of zero? a.|choosing a letter from the alphabet that has line symmetry|c.|choosing a pair of parallel lines that have unequal slopes| b.|choosing a number that is greater than 6 and is even|d.|choosing a triangle that is both
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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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guys‚ this is the probability Assignment. Last date for submission is 10 aug... Q1. What is the probability of picking a card that was either red or black? Q2. A problem in statistics is given to 5 students A‚ B‚ C‚ D‚ E. Their chances of solving it are ½‚1/3‚1/4‚1/5‚1/6. What is the probability that the problem will be solved? Q3. A person is known to hit the target in 3 out of 4 shots whereas another person is known to hit the target in 2 out of 3 shots. Find the probability that the target
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be able to ONEDefine probability. TWO Describe the classical‚ empirical‚ and subjective approaches to probability. THREEUnderstand the terms experiment‚ event‚ outcome‚ permutation‚ and combination. FOURDefine the terms conditional probability and joint probability. FIVE Calculate probabilities applying the rules of addition and multiplication. SIXUse a tree diagram to organize and compute probabilities. SEVEN Calculate a probability using Bayes theorem. What is probability There is really no answer
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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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t) P (X > s + t) P (X > t) e−λ(s+t) e−λt e−λs P (X > s) – Example: Suppose that the amount of time one spends in a bank is exponentially distributed with mean 10 minutes‚ λ = 1/10. What is the probability that a customer will spend more than 15 minutes in the bank? What is the probability that a customer will spend more than 15 minutes in the bank given that he is still in the bank after 10 minutes? Solution: P (X > 15) = e−15λ = e−3/2 = 0.22 P (X > 15|X > 10) = P (X > 5) = e−1/2 =
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Karan negi 12.2 12.3 We use equation 2 to find out probability: F(t)=1 – e^-Lt 1-e^-(0.4167)(10) = 0.98 almost certainty. This shows that probability of another arrival in the next 10 minutes. Now we figure out how many customers actually arrive within those 10 minutes. If the mean is 0.4167‚ then 0.4167*10=4.2‚ and we can round that to 4. X-axis represents minutes (0-10) Y-axis represents number of people. We can conclude from this chart that the highest point with the most visitors
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