Probability 1.) AE-2 List the enduring understandings for a content-area unit to be implemented over a three- to five- week time period. Explain how the enduring understandings serve to contextualize (add context or way of thinking to) the content-area standards. Unit: Data and Probability Time: 3 weeks max Enduring Understanding: “Student Will Be Able To: - Know what probability is (chance‚ fairness‚ a way to observe our random world‚ the different representations) - Know what the
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QMT200 CHAPTER 3: PROBABILITY DISTRIBUTION 3.1 RANDOM VARIABLES AND PROBABILITY DISTRIBUTION Random variables is a quantity resulting from an experiment that‚ by chance‚ can assume different values. Examples of random variables are the number of defective light bulbs produced during the week and the heights of the students is a class. Two types of random variables are discrete random variables and continuous random variable. 3.2 DISCRETE RANDOM VARIABLE A random variable is called
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Probability 2 Theory Probability theory is the branch of mathematics concerned with probability‚ the analysis of random phenomena. (Feller‚ 1966) One object of probability theory is random variables. An individual coin toss would be considered to be a random variable. I predict if the coin is tossed repeatedly many times the sequence of it landing on either heads or tails will be about even. Experiment The Experiment we conducted was for ten students to flip a coin one hundred times
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Introduction Objectives PROBABILITY 2.2 Some Elementary Theorems 2.3 General Addition Rule 2.4 Conditional Probability and Independence 2.4.1 Conditional Probability 2.4.2 Independent Events and MultiplicationRule 2.4.3 Theorem of Total Probability and Bayes Theorem 2.5 Summary 2.1 INTRODUCTION You have already learnt about probability axioms and ways to evaluate probability of events in some simple cases. In this unit‚ we discuss ways to evaluate the probability of combination of events
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1/08/13 Probability Primer Principles of Econometrics‚ 4th Edition Probability Primer Page 1 ! Announcement: ! Please make sure you know who your tutor is and remember their names. This will save confusion and embarrassment later. ! Kai Du (David) ! Ngoc Thien Anh Pham (Anh) ! Zara Bomi Shroff Principles of Econometrics‚ 4th Edition Probability Primer Page 2 Chapter Contents ¡ P.1 Random Variables ¡ P.2 Probability Distributions ¡ P.3 Joint
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Basic Probability Notes Probability— the relative frequency or likelihood that a specific event will occur. If the event is A‚ then the probability that A will occur is denoted P(A). Example: Flip a coin. What is the probability of heads? This is denoted P(heads). Properties of Probability 1. The probability of an event E always lies in the range of 0 to 1; i.e.‚ 0 ≤ P( E ) ≤ 1. Impossible event—an event that absolutely cannot occur; probability is zero. Example: Suppose you roll a normal die
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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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Contents | Page | Part 1 | 2 | Part 2 | 5 | Part 3 | 6 | Part 4 | 8 | Part 5 | 10 | Further Exploration | 13 | Conclusion | 14 | Reflection | 15 | Part 1 a) Introduction The word Probability derives from probity‚ a measure of the authority of a witness in a legal case in Europe‚ and often correlated with the witness ’s nobility. In a sense‚ this differs much from the modern meaning of probability‚ which‚ in contrast‚ is used as a measure of the weight of empirical evidence
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Technology & Science‚ Pilani Work-Integrated Learning Programmes Division Second Semester 2010-2011 Course Handout Course Number Course Title : AAOC ZC111 : Probability and Statistics Course E-mail address : aaoczc111@dlpd.bits-pilani.ac.in Course Description Probability spaces; conditional probability and independence; random variables and probability distributions; marginal and conditional distributions; independent random variables‚ mathematical exceptions‚ mean and variance‚ Binomial Poisson and normal
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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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