2103 CHAP 4 PROB DISTRIBS OCT 11, 13, 15, 18, 20 FALL 2010

# 2103 CHAP 4 PROB DISTRIBS OCT 11, 13, 15, 18, 20 FALL 2010...

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Chapter 4: Random Variables and Probability Distributions Sec 4.1 Two Types of Random Variables: Discrete and Cont Sec. 4.2 Probability Distributions for Discrete Random Variab Mean or Expected Value of a Discrete Random Varia Variance of a discrete Random Variable Standard Deviation of a discrete Random Variable X = # of major defects per automobile upon delivery X P(X) 0 0.10 1 0.30 2 0.30 3 0.20 4 0.10 Sec. 4.3 Binomial Probability Distribution Characteristics of a Binomial Experiment 1. experiment consists of n identical trials 2. There are only 2 possible outcomes on each trial, 3. Probability for both S, and F, remain the same (co P(Success) = P, P(failure) = (1-P) = Q 4. Trials are independent events (outcomes from on 5. The Binomial random variable, X, is the number o Formula for binomial Probability Distribution for P(X Mean, Variance, and Standard Deviation for a Binom Using Binomial Probability Tables Using Excel to determine binomial probabilities Sec. 4.5 Probability Distributions for Continuous Random Va The Standard Normal Distribution Property of Normal Distribution, Z score formula Using the Normal Probability Distribution Tables

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Using Excel to Find Normal Probabilities, etc. Applic. #1. Steps for finding a probability correspon Applic #2. Given Probability of X, solve for X X= MPG Assume MPG is a Normal Random Variable Mean= 30mpg SDEV= 1.5mpg
tinuous bles able l, such as S=Success, and F=Failure onstant) from trial to trial. e trial to the next are independent events) of S's (successes) in "n" trials. X=x) ial Random Variable ariables

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nding to a Normal Random Variable
EXAM ONE ANSWER SHEETS (BLUE SCANTRONS) AVAI ANSWERS TO EXAM ONE WERE DISCUSSED DURING FR EXAM ONE GRADES WERE POSTED LAST THURSDAY O REMINDER: EACH VISIT TO PEER TEACHER OFFICE HOU UP TO 2% ADDED TO COURSE GRADE AT EN WHICH IS ABOUT 1 PER WEEK, OR NEARLY PEER TEACHER HOURS TODAY ARE 10:30 TO NOON, SP Chapter 4: Random Variables and Probability Distribution Sec 4.1 Two Types of Numeric Random Variables: Dis Numeric Random Variable is one for which it i Discrete: Numeric random variables which ca Continuous: Numeric random variables which Discrete Random Variables: 1) Number of children per household; the aver 2) Number of defects per shipment 3) Number of promotions per employee Continuous Random Variables 1) things that are measured, e.g., Volume, Wei 2) Physical measures, dimensions, etc. e.g., Time to connect to internet; 2 3 4 5 values such as 2.4, 2.45, 2.453, a Number of decimal places is rela Sec. 4.2 Probability Distributions for Discrete Random a) Mean or Expected Value of a Discrete Rand

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Variance of a discrete Random Variable Standard Deviation of a discrete Random Vari X = # of major defects per automobile upon delivery # of Def's X P(X) X*P(X) X*P(X) 0 0.10 (0*0.10)= 0.0000 1 0.30 (1*0.30)= 0.3000 2 0.30 etc. 0.6000 3 0.20 0.6000 4 0.10 0.4000 1.0000 Mean=E(x)= 1.9 a) Mean or Expected Value of a Discrete Random Variable Can we simply add up the "X" values and divi
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## This note was uploaded on 03/29/2011 for the course STAT 2103 taught by Professor Pred during the Fall '10 term at Temple.

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2103 CHAP 4 PROB DISTRIBS OCT 11, 13, 15, 18, 20 FALL 2010...

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