Unit 4 Starters. Starter 7.1.1 Suppose a fair coin is tossed 4 times. Find the probability that heads comes up exactly two times.

Slides:



Advertisements
Similar presentations
The Binomial and Geometric Distributions Chapter 8.
Advertisements

Lesson Objective Be able to calculate probabilities for Binomial situations Begin to recognise the conditions necessary for a Random variable to have a.
Chapter 8 Counting Principles: Further Probability Topics Section 8.5 Probability Distributions; Expected Value.
Chapter 7 Discrete Distributions. Random Variable - A numerical variable whose value depends on the outcome of a chance experiment.
Statistics Chapter 3: Introduction to Discrete Random Variables.
The Geometric Distributions Section Starter Fred Funk hits his tee shots straight most of the time. In fact, last year he put 78% of his.
Chapter – Binomial Distributions Geometric Distributions
Prof. Bart Selman Module Probability --- Part d)
Binomial & Geometric Random Variables
Warm-up The mean grade on a standardized test is 88 with a standard deviation of 3.4. If the test scores are normally distributed, what is the probability.
Binomial PDF and CDF Section Starter Five marbles are on a table. Two of them are going to be painted with a “W” and the rest will be painted.
Random Variables A random variable A variable (usually x ) that has a single numerical value (determined by chance) for each outcome of an experiment A.
Chapter 6: Probability Distributions
Lesson 8 – R Taken from And modified slightlyhttp://
5.5 Distributions for Counts  Binomial Distributions for Sample Counts  Finding Binomial Probabilities  Binomial Mean and Standard Deviation  Binomial.
Binomial Distributions Calculating the Probability of Success.
Chapter 4 Probability Distributions
Copyright © 2006 Brooks/Cole, a division of Thomson Learning, Inc.
IE241 Problems. 1. Three fair coins are tossed in the air. What is the probability of getting 3 heads when they land?
Section 6.3 Binomial Distributions. A Gaggle of Girls Let’s use simulation to find the probability that a couple who has three children has all girls.
P. STATISTICS LESSON 8.2 ( DAY 1 )
DMR #21 (a) Find the probability that a randomly chosen household has at least two televisions: (b) Find the probability that X is less than 2.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Mistah Flynn.
Probability Distribution
40S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Statistics Lesson: ST-5 The Binomial Distribution The Binomial Distribution Learning Outcome.
Discrete Distributions. Random Variable - A numerical variable whose value depends on the outcome of a chance experiment.
At the end of the lesson, students can: Recognize and describe the 4 attributes of a binomial distribution. Use binompdf and binomcdf commands Determine.
L56 – Discrete Random Variables, Distributions & Expected Values
AP Statistics Monday, 30 November 2015 OBJECTIVE TSW begin the study of discrete distributions. EVERYONE needs a calculator. The tests are graded.
Binomial Probability Section Starter Here’s a game you will like: Let’s bet a dollar on this proposition: I will roll a fair die once. If.
Chapter 16 Week 6, Monday. Random Variables “A numeric value that is based on the outcome of a random event” Example 1: Let the random variable X be defined.
1 Keep Life Simple! We live and work and dream, Each has his little scheme, Sometimes we laugh; sometimes we cry, And thus the days go by.
Binomial Distributions Chapter 5.3 – Probability Distributions and Predictions Mathematics of Data Management (Nelson) MDM 4U.
Review Know properties of Random Variables
The Mean of a Discrete Random Variable Lesson
Chapter 6: Random Variables
Combining Two Random Variables: Means and Variances Lesson
6.1 Discrete and Continuous Random Variables Objectives SWBAT: COMPUTE probabilities using the probability distribution of a discrete random variable.
Binomial Distributions Chapter 5.3 – Probability Distributions and Predictions Mathematics of Data Management (Nelson) MDM 4U Authors: Gary Greer (with.
6.3 Binomial and Geometric Random Variables
Unit 4 Review. Starter Write the characteristics of the binomial setting. What is the difference between the binomial setting and the geometric setting?
Simulations with Binomials Mean and S.D. of Binomials Section
Section 6.3 Day 1 Binomial Distributions. A Gaggle of Girls Let’s use simulation to find the probability that a couple who has three children has all.
1 Chapter 4 Mathematical Expectation  4.1 Mean of Random Variables  4.2 Variance and Covariance  4.3 Means and Variances of Linear Combinations of Random.
+ Binomial and Geometric Random Variables Textbook Section 6.3.
Chapter 8: The Binomial and Geometric Distributions 8.2 – The Geometric Distributions.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright © 2009 Pearson Education, Inc. Chapter 17 Probability Models.
Lesson 96 – Expected Value & Variance of Discrete Random Variables HL2 Math - Santowski.
Chapter 8: The Binomial and Geometric Distributions 8.1 – The Binomial Distributions.
Discrete Distributions
Chapter Five The Binomial Probability Distribution and Related Topics
3 Discrete Random Variables and Probability Distributions
Probability 5: Binomial Distribution
Lesson Objective Be able to calculate probabilities for Binomial situations Begin to recognise the conditions necessary for a Random variable to have a.
Probability Distributions; Expected Value
CHAPTER 6 Random Variables
Lesson Objectives At the end of the lesson, students can:
Chapter 16.
Probability distributions
Discrete Distributions
Discrete Distributions
Continuous Random Variable Normal Distribution
Discrete Distributions.
Elementary Statistics
Chapter 6 Random Variables
Discrete Distributions
Review of the Binomial Distribution
Review of Chapter 8 Discrete PDFs Binomial and Geometeric
Presentation transcript:

Unit 4 Starters

Starter Suppose a fair coin is tossed 4 times. Find the probability that heads comes up exactly two times.

Answer A tree diagram will show that there are 16 possible outcomes. The tree diagram also shows that 6 branches contain exactly two heads. Therefore P(two H) = 6/16 Another approach: –There are 2x2x2x2=16 outcomes from 4 flips –Choose any two flips to be heads: 4 C 2 =6 –So P(two H) = 6/16

Starter A 9-sided die has three faces that show 1, two faces that show 2, and one face each showing 3, 4, 5, 6. Let X be the number that shows face-up. Draw the PDF histogram of X.

Answer What is the total area under the histogram? (3/9) + (2/9) + 4 x (1/9) = 9/9 = 1

Starter What is the difference between a discrete random variable and a continuous random variable? –There are two important ideas here Assume a certain continuous random variable X is known to be N(55, 1.2). If you randomly choose one observation of X, what is the probability that: a)X < 55 b)X < 53 c)X > 53 Hint: normalcdf(LB, UB, mean, s.d.)

Answer A discrete random variable has a finite number of outcomes that can only take on specific (usually integer) values. It can be represented by a table or histogram. A continuous random variable has an infinite number of outcomes. We can never list them all, and they typically include rational and irrational decimals. It can be represented by a density curve (only). P(X<55) =.5 by definition: 55 is the median P(X<53) = normalcdf(0, 53, 55, 1.2) =.0478 P(X>53) = 1 –.0478 =.9521

Starter An unfair six-sided die comes up 1 on half of its rolls. The other half of its rolls are evenly spread through the other 5 outcomes. If X is the number that comes up, write PDF for X.

Answer X P(X).5.1

Starter Calculate from formula the variance of these data: 1, 2, 3, 4, 5

Answer

Starter Suppose I measure the heights of a class of fourth-graders and find the distribution of heights to be N(100, 2 cm). Then I have them all stand on top of a 10 cm high step and I measure again. What change would you expect in the mean? What change would you expect in the standard deviation?

Answer Since we added 10 to all values, the mean should increase by 10 cm. Adding 10 to all values did not change the spread; it just changed the location if we plotted on an axis. So we expect the standard deviation to remain unchanged at 2.

Starter A bag contains 4 red marbles and one white marble. Two marbles are chosen without replacement. What is the probability that they are both red? A worker is paid each week in the following manner: He draws two bills from a bag which contains four $20 bills and one $100 bill. What is the expected outcome of his average weekly pay over the long run?

Answer Let X = the amount of weekly pay –Notice that X can only be $40 or $120 There are 5 C 2 (= 10) ways to draw two bills from the five in the bag There are 4 C 2 (= 6) ways to draw two $20 bills from the four in the bag –So P(40) = 6/10 There are 4 ways to draw one $100 and one $20 –So P(120) = 4/10 E(X) = $40 (6/10) + $120 (4/10) = $72

Starter Here’s a game you will like: Let’s bet a dollar on this proposition: I will roll a fair die once. If it comes up 1 or 2, I win. If it comes up 3, 4, 5, or 6, you win! –What is the probability that I win? –What is the probability that I lose? –How much should we each bet to make this a fair game?

Answer P(win) = 2/6 or 1/3 P(lose) = 4/6 or 2/3 Odds that I win are 2:4 (or 1:2) against, so you should bet $2 and I bet $1 –Note: “fair” in this context means E(x) =0, where x represents my net winnings. –E(x) = (+2)(1/3) + (-1)(2/3) = 0, so it’s fair

Starter Five white marbles are on a table. Two of them are to be painted with a “W” and the rest will be painted with a “L”. How many ways are there to choose the two marbles to be painted “W”?

Starter A baseball player bats.325 over a full season. If he bats 5 times today, find the probability he gets at least 3 hits.

Answer This is a binomial setting, so use the binomial CDF of at most 2 hits, then subtract from 1 1 – binomcdf(5,.325, 2) =.197

Starter A manufacturer produces a large number of toasters. From past experience, he knows that about 2% are defective. In a quality control procedure, we randomly select 20 toasters for testing. We want to determine the probability that no more than one of these toasters is defective. –Is this a binomial setting? Justify your answer. –Find the probability that exactly one toaster is defective. –Find the probability that at most one toaster is defective. –Find the mean and standard deviation for the problem.

Answer Two outcomes (good / defective), a fixed number of trials (20), independent trials, probability is fixed (2%), so it is binomial. P(X=1) = binompdf(20,.02, 1) = 27% P(X  1) = binomcdf(20,.02, 1) = 94% μ = np = (20)(.02) =.4 –So we expect on average.4 defectives in each group of 20 σ = √npq = √(20)(.02)(.98) =.626

Starter Fred Funk hits his tee shots straight most of the time. In fact, last year he put 78% of his tee shots in the fairway. In yesterday’s round, he hit only 7 of 14 shots in the fairway. What is the likelihood that he would have that bad a day (or worse) from the tee?

Answer This is a binomial setting –There are 14 trials where he succeeds or fails at hitting the fairway –All trials are independent with fixed probability To do this poorly (or worse) means he hits at most 7 fairways. –He could hit 7 or 6 or 5 or … Binomcdf(14,.78, 7) =.02 –So there is only a 2% chance he will do that poorly.

Starter The SAT Math and Verbal sections are both designed to be approximately normal with a mean of 500 and standard deviation of 100. If we defined a new measure (TOTAL) by adding the scores on the two sections, what would you expect the mean and standard deviation of TOTAL to be? (Assume math and verbal are independent)

Answer

Starter Write the characteristics of the binomial setting. What is the difference between the binomial setting and the geometric setting?

Answer The binomial setting has 4 characteristics: –There are only two possible outcomes –Each trial has fixed probability of success –Each trial is independent of all other trials –There are a fixed number of trials; the variable of interest is the number of successes The geometric setting has the same first three characteristics. The difference is in the fourth: there are an unknown number of trials; trials stop after the first success; the variable of interest is the number of trials until the first success