CHAPTER 7 DAY 1. Warm – Up (Density Curves Review)  Consider the density curve that consists of two line segments. The first segment starts at the point.

Slides:



Advertisements
Similar presentations
AP Statistics Chapter 7 – Random Variables. Random Variables Random Variable – A variable whose value is a numerical outcome of a random phenomenon. Discrete.
Advertisements

AP Statistics Chapter 7 Notes. Random Variables Random Variable –A variable whose value is a numerical outcome of a random phenomenon. Discrete Random.
A.P. STATISTICS LESSON 7 – 1 ( DAY 1 ) DISCRETE AND CONTINUOUS RANDOM VARIABLES.
Random Variables.
Random Variables November 23, Discrete Random Variables A random variable is a variable whose value is a numerical outcome of a random phenomenon.
1 Continuous random variables f(x) x. 2 Continuous random variables A discrete random variable has values that are isolated numbers, e.g.: Number of boys.
CHAPTER 10: Introducing Probability
Objective: Objective: Use experimental and theoretical distributions to make judgments about the likelihood of various outcomes in uncertain situations.
Week71 Discrete Random Variables A random variable (r.v.) assigns a numerical value to the outcomes in the sample space of a random phenomenon. A discrete.
L7.1b Continuous Random Variables CONTINUOUS RANDOM VARIABLES NORMAL DISTRIBUTIONS AD PROBABILITY DISTRIBUTIONS.
7.1 Discrete and Continuous Random Variable.  Calculate the probability of a discrete random variable and display in a graph.  Calculate the probability.
Chapter 7 Random Variables I can find the probability of a discrete random variable. 6.1a Discrete and Continuous Random Variables and Expected Value h.w:
Applied Business Forecasting and Regression Analysis Review lecture 2 Randomness and Probability.
5.3 Random Variables  Random Variable  Discrete Random Variables  Continuous Random Variables  Normal Distributions as Probability Distributions 1.
Chapter 5.1 Probability Distributions.  A variable is defined as a characteristic or attribute that can assume different values.  Recall that a variable.
Chapter 5: Random Variables and Discrete Probability Distributions
Special Topics. Mean of a Probability Model The mean of a set of observations is the ordinary average. The mean of a probability model is also an average,
Probability Distributions. We need to develop probabilities of all possible distributions instead of just a particular/individual outcome Many probability.
The Practice of Statistics Third Edition Chapter 7: Random Variables Copyright © 2008 by W. H. Freeman & Company Daniel S. Yates.
Chapter 7 Random Variables
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
4.1 Probability Distributions NOTES Coach Bridges.
CHAPTER 10: Introducing Probability ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Lecture 8. Random variables Random variables and probability distributions Discrete random variables (Continuous random variables)
Chapter 16 Probability Models. Who Wants to Play?? $5 to play You draw a card: – if you get an Ace of Hearts, I pay you $100 – if you get any other Ace,
Chapter 7 Continuous Distributions Notes page 137.
Essential Statistics Chapter 91 Introducing Probability.
CHAPTER 10 Introducing Probability BPS - 5TH ED.CHAPTER 10 1.
Chapter 10 Introducing Probability BPS - 5th Ed. Chapter 101.
Modeling Discrete Variables Lecture 22, Part 1 Sections 6.4 Fri, Oct 13, 2006.
Warm Up: 2003 AP FRQ #2. We usually denote random variables by capital letters such as X or Y When a random variable X describes a random phenomenon,
Random Variables Ch. 6. Flip a fair coin 4 times. List all the possible outcomes. Let X be the number of heads. A probability model describes the possible.
BPS - 3rd Ed. Chapter 91 Introducing Probability.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 6: Random Variables Section 6.1 Discrete and Continuous Random Variables.
AP STATISTICS Section 7.1 Random Variables. Objective: To be able to recognize discrete and continuous random variables and calculate probabilities using.
Section 7.1 Discrete and Continuous Random Variables
Chap 7.1 Discrete and Continuous Random Variables.
Chapter 4 Discrete Probability Distributions 1 Larson/Farber 4th ed.
CHAPTER 10: Introducing Probability ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
1 Chapter 10 Probability. Chapter 102 Idea of Probability u Probability is the science of chance behavior u Chance behavior is unpredictable in the short.
MATH Section 3.1.
Copyright ©2011 Brooks/Cole, Cengage Learning Random Variables Class 34 1.
AP Statistics, Section 7.11 The Practice of Statistics Third Edition Chapter 7: Random Variables 7.1 Discete and Continuous Random Variables Copyright.
Discrete and Continuous Random Variables Section 7.1.
Discrete Probability Distributions Chapter 4. § 4.1 Probability Distributions.
Section Discrete and Continuous Random Variables AP Statistics.
Unit 5 Section 5-2.
Discrete Probability Distributions
Discrete and Continuous Random Variables
AP Statistics: Chapter 7
WARM – UP 1.) In a box of 10 batteries, 3 batteries are Dead. You choose 2 batteries from the box at random: a) Create the probability model for the.
CHAPTER 10: Introducing Probability
Review for test Ch. 6 ON TUESDAY:
Chapter 10 - Introducing Probability
Warm Up Imagine you are rolling 2 six-sided dice. 1) What is the probability to roll a sum of 7? 2) What is the probability to roll a sum of 6 or 7? 3)
Uniform Distributions and Random Variables
Discrete Probability Distributions
MATH 2311 Section 3.1.
Modeling Discrete Variables
AP Statistics Chapter 16 Notes.
7.1: Discrete and Continuous Random Variables
Discrete & Continuous Random Variables
Essential Statistics Introducing Probability
Probability Distributions
Continuous Random Variables
Chapter 4 Probability.
Modeling Discrete Variables
MATH 2311 Section 3.1.
Presentation transcript:

CHAPTER 7 DAY 1

Warm – Up (Density Curves Review)  Consider the density curve that consists of two line segments. The first segment starts at the point (0,2) and ends at the point (0.4,1). The second segments begin at (0.4,1) and ends at (0.8,1).  1. Verify that this is a valid density curve.  2. Use the area under the density curve to find the proportions of observations within the given intervals.  A. P(0.6 < X < 0.8)  B. P(0 < X < 0.4)  C. P(0 ≤ X ≤ 0.2)  D. P(X = 0.5)

Continuous vs. Discrete  Continuous is measured, infinite  Discrete is counted, finite

Continuous vs. Discrete  Gliding down a slide  Pouring water  Length of a rope  Age of students  Seasonal rainfall  Distance of a race  Time playing a CD  Segment on a graph  Climbing up stairs  Stacking ice cubes  Number of knots  Number of your birthday  Rainy days  Number of participants  Points on a graph

Random Variable  A random variable is a variable whose value is a numerical outcome of a random phenomenon.

Discrete Random Variable  A discrete random variable X has a countable number of possible values. The probability distribution of a discrete random variable X lists the values and their probabilities. Value of Xx1x1 x2x2 x3x3 …xixi Probabilityp1p1 p2p2 p3p3 …pipi

Discrete Random Variable Cont…  The probability p must satisfy two requirements:  1. Every probability p i is a number between 0 and 1.  2. The sum of the probabilities is 1.  Find the probability of an event by adding the probabilities p i of the particular values x i that make up that event.

Example #2 from Homework  A couple plans to have three children. There are 8 possible arrangements of girls or boys. For example GGB means the first two children are girls and the third is a boy. All 8 arrangements are equally likely.  A. Write down all 8 arrangements. What is the probability of any one of these arrangements?  Let X be the number of girls the couple has. What is the probability that X = 2?  Starting from your work in A, find the distribution of X. That is, what values can X take, and what are the probabilities for each value. (make a table and histogram)

Example #6 from Homework  Choose an American household at random and let the random variable X be the number of persons living in the household. If we ignore the few houses with more than 7 inhabitants, the probability distribution of X is as follows. Inhabitants Probability

 Verify that this is a legitimate discrete probability distribution and draw a probability histogram to display it.  What is P(X ≥ 5)?  What is P(X > 5)?  What is P(2 < X < 4)?  What is P(X ≠ 1)?  Write the event that a randomly chosen household contains more than two persons in terms of the random variable X. What is the probability of this event?