TAMU MATH 141 - 141_notes_Ch8 (12 pages)

Previewing pages 1, 2, 3, 4 of 12 page document View the full content.
View Full Document

141_notes_Ch8



Previewing pages 1, 2, 3, 4 of actual document.

View the full content.
View Full Document
View Full Document

141_notes_Ch8

154 views


Pages:
12
School:
Texas A&M University
Course:
Math 141 - Business Math I
Business Math I Documents
Unformatted text preview:

Chapter 8 Probability Distributions and Statistics Section 8 1 Distributions of Random Variables The value of the result of the probability experiment is a RANDOM VARIABLE If you roll a die we can let X be the number of dots showing If we have a hand of three cards X could be the number of clubs in the hand These examples are all finite discrete random variables Example Roll a single die and count the number of rolls until a 6 comes up outcome Y Finally the random variable can be continuous Example You are dealt a hand of 5 cards Find the probability distribution table for the number of hearts Graph this in a histogram 8 2 Expected Value The expected value for the variable X in a probability distribution is What is the MEAN of X E X X1 P X1 X 2 P X 2 X n P X n Example You are dealt a hand of 5 cards What is the expected number of hearts What was the X value that happened the most often What was the X value that was in the middle Example A sample of mini boxes of raisin bran cereal was selected and the number of raisins in each box was counted The results are shown in the table below of boxes 13 14 15 16 17 of raisins 10 14 19 16 12 Determine the appropriate random variable X and display the data in a probability histogram What is the expected value of X What is the RANGE of X values Histograms and Averages The MEAN expected value is where the histogram balances The MODE is the tallest rectangle The MEDIAN is where the area is cut in half The RANGE is the number of rectangles remember some may have a height of 0 Example Find the mean median and mode of the following test scores 77 46 98 87 84 62 71 80 66 59 79 89 52 94 77 72 85 90 64 70 Mean Median Mode Range Another way to measure spread QUARTILES 46 52 59 62 64 66 70 71 72 77 77 79 80 84 85 87 89 90 94 98 Q1 Q3 Box and whisker plot IQR Example A game consists of choosing two bills at random from a bag containing 7 one dollar bills and 3 ten dollar bills The player gets to keep the money picked How much should be charged to play this game to keep it fair expected value of zero Example From a group of 2 women and 5 men a delegation of 2 is chosen Find the expected number of women in the delegation ODDS 8 3 Variance and Standard Deviation If P E is the probability of event E occurring then the odds in favor of E are 33333 22344 P E P E P E 1 1 P E P E c We usually express the odds as a ratio of whole numbers a b a to b a b Example If the probability that the Aggies will win a football game is 80 what are the odds in favor of the Aggies POPULATION VARIANCE If we are given the odds we want to be able to find the probability if the odds in favor of E are given as a b then P E a a b Odds to win the Breeders Cup Distaff Saturday November 4th 2006 Siempre 29 5 Balletto 7 5 Fleet Indian 2 1 Happy Ticket 21 2 Round Pond 22 1 Spun Sugar 11 1 Bushfire 18 1 Summerly30 1 POPULATION STANDARD DEVIATION 00555 What do we mean by population This means everyone so if ALL the members of the population are used to find the mean we use the symbols m and s Example An exam has an mean of m 75 and a population standard deviation of s 14 2 The mean from SAMPLE uses the symbol x 1 0 SAMPLE STANDARD DEVIATION When we have the probability it is assumed we had the entire population to base it on so it is appropriate to use m and s Example Find the mean and standard deviation for the following distribution 45 50 55 60 65 70 75 80 85 90 95 100 What is the probability that a randomly chosen data point is within 1 standard deviation of the mean What is the probability that a randomly chosen data point is within 2 standard deviations of the mean 2 1 0 45 50 55 60 65 70 75 80 85 90 95 100 Chebychev s Theorem For any data distribution with mean m and standard deviation s the probability that a randomly chosen data point is within m k s to m k s is at least 1 1 k2 Or 1 P m k s x m k s 1 2 k Example A probability distribution has a mean of 50 and a standard deviation of 5 a What is the probability that an outcome of the experiment lies between 35 and 65 8 4 The Binomial Distribution In a Bernoulli trial we have the following The same experiment repeated several times The only possible outcomes of these experiments are success or failure The repeated trials are independent so the probability of success remains the same for each trial Example A multiple choice test has 3 questions each with 4 possible answers A student guesses on each question What is the probability that the student gets exactly two questions correct b Find the value of k so that at least 93 75 of the data lies in the range 50 5k to 50 5k BINOMIAL PROBABILITY If p is the probability of success in a single trial of a binomial Bernoulli experiment the probability of x successes and n x failures in n independent repeated trials of the same experiment is Example The first half of July was very dry in college station If each day there was a 20 chance of rain what is the probability of no rain in the first 15 days in July What is the probability of at most 2 rain days x number of successes DEFINE SUCCESS n number of trials x number of successes p probability of success binomcdf n p x will give you the sum of the probabilities from 0 to x binompdf n p x on the calculator For a binomial probability question you must do the following Decide that it is a Bernoulli trial Define what success is Find the number of times the experiment is done n Find the probability of success p Determine the number of successes you need to find x Example A new drug being tested causes a serious side effect in 5 of patients What is the probability that in a sample of 10 patients none get the side effect from taking the drug define success no side effect n number of trials x number of successes p probability of success define success side effect n number of trials x number of successes p probability of success If X is a binomial random variable associated with a binomial experiment consisting of …


View Full Document

Access the best Study Guides, Lecture Notes and Practice Exams

Loading Unlocking...
Login

Join to view 141_notes_Ch8 and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view 141_notes_Ch8 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?