Modelling 2 Week 3: Discrete Random Variables Stephen Bush Department of Mathematical Sciences MM2: Statistics - Week 3 - 1 Random Variables • Reference: Devore § 3.1 – 3.5 • Definitions: • An experiment is any process of obtaining one outcome where the outcome is uncertain. • A random variable is a numerical variable whose value can change from one replicate of the experiment to another. • Sample means and sample standard deviations are random variables • They are different
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Colorado Technical University Phase 1-DB-Concepts and Terminology of Statistics Applied to Business Decision Making MGMT600-1403A-04: Applied Managerial Decision-Making with Robert Throop. 8 July 2014 Reused: This task was originally submitted during the previous session‚ Term 1402B‚ in MGMT600-01 with Priscilla Johnson. I. Introduction WidgeCorp became an industry front-runner in snacks when it obtained Company W. The administration styles varied significantly. WidgeCorp managers gathered
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Discrete Random Variables: Homework Exercise 1 Complete the PDF and answer the questions. |X |P(X = x) |X(P(X = x) | |0 |0.3 | | |1 |0.2 | | |2 | | | |3 |0.4 | | a. Find the probability that X = 2. b. Find the expected value. Exercise 2 Suppose that you are offered the following “deal.” You roll a die. If you
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is a continuous random variable because the time is being measured. All possible results for the variable time (t) would be greater than > 0. b) The weight of a T-bone steak is a continuous random variable because the weight of the steak is measured. All the possible results for the weight of the T-bone steak would be positive numbers making the variable weight (w) > greater than 0. c) The number of free throw attempts before the first shot is made is a discrete random
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STA1101 Normal Distribution and Continuous random variables CONTINUOUS RANDOM VARIABLES A random variable whose values are not countable is called a _CONTINUOUS RANDOM VARIABLE._ THE NORMAL DISTRIBUTION The _NORMAL PROBABILITY DISTRIBUTION_ is given by a bell-shaped(symmetric) curve. THE STANDARD NORMAL DISTRIBUTION The normal distribution with and is called the _STANDARD NORMAL DISTRIBUTION._ Example 1: Find the area under the standard normal curve between z = 0 and z = 1.95 from z
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Discrete and Continuous Probability All probability distributions can be categorized as discrete probability distributions or as continuous probability distributions (stattrek.com). A random variable is represented by “x” and it is the result of the discrete or continuous probability. A discrete probability is a random variable that can either be a finite or infinite of countable numbers. For example‚ the number of people who are online at the same time taking a statistics class at CTU on
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TEM1116 Probability and Statistics Tri1 2013/14 Chapter 1 Chapter 1: Discrete and Continuous Probability Distributions Section 1: Probability Contents: 1.1 1.2 1.3 1.4 1.5 Some basics of probability theory Axioms‚ Interpretations‚ and Properties of Probability Counting Techniques and Probability Conditional Probability Independence TEM1116 1 TEM1116 Probability and Statistics Tri1 2013/14 Chapter 1 1.1 Basics of Probability Theory Probability refers to the study
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WHAT IS A RANDOM VARIABLE? A random variable assigns a number to each outcome of a random circumstance‚ or‚ equivalently‚ a random variable assigns a number to each unit in a population. It is easier to create rules for broad classes of situations and then identify how a specific example fits into a class than it is to create rules for each specific example. We can employ this strategy quite effectively for working with a wide variety of situations Involving probability and random outcomes. We
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Question 1 .5 out of 5 points The __________ is the maximum value that one would be willing to pay for additional information Answer Selected Answer: expected value of perfect information . Question 2 .0 out of 5 points The credit scores of a certain population are approximately normally distributed with a mean of 645 points and a standard deviation of 65 points. The credit score of an individual should belong to the top 5% of the credit scores in order to qualify for a home loan
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THE MOMENTS OF A RANDOM VARIABLE Definition: Let X be a rv with the range space Rx and let c be any known constant. Then the kth moment of X about the constant c is defined as Mk (X) = E[ (X c)k ]. (12) In the field of statistics only 2 values of c are of interest: c = 0 and c = . Moments about c = 0 are called origin moments and are denoted by k‚ i.e.‚ k = E(Xk )‚ where c = 0 has been inserted into equation (12). Moments about the
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