Warm-up 5.1 Introduction to Probability 1) 2) 3) 4) 5) 6) 7)

Slides:



Advertisements
Similar presentations
Chapter 5- Probability Review
Advertisements

Chapter 3 Probability.
Larson/Farber 4th ed 1 Basic Concepts of Probability.
1-1 Copyright © 2015, 2010, 2007 Pearson Education, Inc. Chapter 13, Slide 1 Chapter 13 From Randomness to Probability.
AP STATISTICS Simulation “Statistics means never having to say you're certain.”
AP STATISTICS Simulating Experiments. Steps for simulation Simulation: The imitation of chance behavior, based on a model that accurately reflects the.
Chapter 6 Probability and Simulation
Randomness and Probability
Section 5.1 and 5.2 Probability
From Randomness to Probability
Section 4-2 Statistics 300: Introduction to Probability and Statistics.
CORE 1 Patterns in Chance. Daily Starter Begin Handout.
1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 13 = Finish Chapter “ Basic Probability” (BP) Agenda:
Learning Goal 13: Probability Use the basic laws of probability by finding the probabilities of mutually exclusive events. Find the probabilities of dependent.
© 2013 Pearson Education, Inc. Active Learning Lecture Slides For use with Classroom Response Systems Introductory Statistics: Exploring the World through.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
CORE 1 Patterns in Chance. Daily Starter Begin Handout.
Section 1.2 Continued Discrimination in the Workplace: Inference through Simulation: Discussion.
Chapter 6 Probabilit y Vocabulary Probability – the proportion of times the outcome would occur in a very long series of repetitions (likelihood of an.
Chapter 1 Basics of Probability.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Basic Principle of Statistics: Rare Event Rule If, under a given assumption,
Introduction to Probability
1 Chapters 6-8. UNIT 2 VOCABULARY – Chap 6 2 ( 2) THE NOTATION “P” REPRESENTS THE TRUE PROBABILITY OF AN EVENT HAPPENING, ACCORDING TO AN IDEAL DISTRIBUTION.
The Practice of Statistics
LECTURE 15 THURSDAY, 15 OCTOBER STA 291 Fall
Section Using Simulation to Estimate Probabilities Objectives: 1.Learn to design and interpret simulations of probabilistic situations.
Chapter 9 Review. 1. Give the probability of each outcome.
LECTURE 14 TUESDAY, 13 OCTOBER STA 291 Fall
Lesson 6 – 2b Probability Models Part II. Knowledge Objectives Explain what is meant by random phenomenon. Explain what it means to say that the idea.
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Warm-up 1.2 Introduction to Summary Statistics and Simulation 1.What percentage of recent hires are older than 50? 2.What percentage of hourly recent hires.
WRITE DOWN 5 WAYS IN WHICH YOU SEE/USE PROBABILITY IN EVERY DAY LIFE.
Copyright © 2010 Pearson Education, Inc. Unit 4 Chapter 14 From Randomness to Probability.
Copyright © 2010 Pearson Education, Inc. Slide
From Randomness to Probability Chapter 14. Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes could happen,
Probability Likelihood of an event occurring! Random Circumstances A random circumstance is one in which the outcome is unpredictable. Test results are.
Probability Basics Section Starter Roll two dice and record the sum shown. Repeat until you have done 20 rolls. Write a list of all the possible.
4.3a Simulating Experiments Target Goal: I can use simulation to represent an experiment. In class FR.
Simulating Experiments Introduction to Random Variable.
5.2 Using Simulation to Estimate Probabilities HW: E’s 15, 17, 19, 21.
AP Statistics Wednesday, 20 November 2015 OBJECTIVE TSW review for the test covering probability.
Chapter 4 Probability, Randomness, and Uncertainty.
Simulation Chapter 16 of Quantitative Methods for Business, by Anderson, Sweeney and Williams Read sections 16.1, 16.2, 16.3, 16.4, and Appendix 16.1.
Simulation. Simulation  Simulation imitation of chance behavior based on a model that accurately reflects the phenomenon under consideration  By observing.
Simulation. Simulation is a way to model random events, such that simulated outcomes closely match real-world outcomes. By observing simulated outcomes,
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
5-Minute Check on Section 6-2a Click the mouse button or press the Space Bar to display the answers. 1.If you have a choice from 6 shirts, 5 pants, 10.
Chapter 14 From Randomness to Probability. Dealing with Random Phenomena A random phenomenon: if we know what outcomes could happen, but not which particular.
Chapter 6 - Probability Math 22 Introductory Statistics.
Unit 6 Probability & Simulation: the Study of randomness Simulation Probability Models General Probability Rules.
5-Minute Check on Chapter 5 Click the mouse button or press the Space Bar to display the answers. 1.What can help detect “cause-and-effect” relationships?
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Section Constructing Models of Random Behavior Objectives: 1.Build probability models by observing data 2.Build probability models by constructing.
Chapter 4 Probability and Counting Rules. Introduction “The only two sure things are death and taxes” A cynical person once said.
6.2 – Probability Models It is often important and necessary to provide a mathematical description or model for randomness.
AP STATISTICS LESSON AP STATISTICS LESSON PROBABILITY MODELS.
Probability Models Section 6.2. The Language of Probability What is random? What is random? Empirical means that it is based on observation rather than.
AP Statistics From Randomness to Probability Chapter 14.
Warm-up What is the best way to answer each of the questions below: an experiment, a sample survey, or an observational study that is not a sample survey?
Probability Models Section 6.2.
Section 5.1 and 5.2 Probability
Section 5.3 Day 2.
Experimental Probability vs. Theoretical Probability
Using Simulation to Estimate Probabilities
Statistics 300: Introduction to Probability and Statistics
From Randomness to Probability
Honors Statistics From Randomness to Probability
Section 6.2 Probability Models
Homework: pg. 398 #4, 5 pg. 402 #10, 11 4.) A. A single random digit simulates one shot, 1-7 represents a made shot 8-10 represents a miss. Then 5 consecutive.
I flip a coin two times. What is the sample space?
Presentation transcript:

Warm-up 5.1 Introduction to Probability 1) 2) 3) 4) 5) 6) 7)

Student of the day! Block 1

Student of the day! Block 2

Ch. 5 Vocabulary 1)event 2)complement 3)probability distribution 4)sample spaces 5)disjoint 6)mutually exclusive 7)Law of Large Numbers 8)Fundamental Principle of Counting 9)probability model 10)Property of Disjoint Events 11) Addition Rule of Disjoint Events 12) Addition Rule 13) Conditional Probability 14) Multiplication Rule 15) dependent events 16) independent events 17) Multiplication Rule for independent events

Important Dates on Sharepoint Monday 12/3 5.1 to 5.3 Quiz Friday 12/7 and Tuesday 12/11 Ch. 5 Notebook Check Thursday 12/13 Ch. 5 Test (2 days before Winter Break) Winter Break After winter break: Probability Activity Multiple Choice Practice with Ch. 5 Probability Spend at least 3 days reviewing for the midterm

5.1 Introduction to Probability

Probability Distribution Suppose we want to list the sample space of the result of flipping two coins. If we include the probabilities it is considered a probability distribution. The complement of any event is 1 – P(event). What is the probability of not getting TT or what P( TT c )?

Multiplication Counting Principle The two spinners are mutually exclusive (independent events). Multiplication (Counting) Principle states that by multiplying the possible outcomes in each category, we can find the total number of possible arrangements.

Law of Large Numbers Let’s say you suspect your friend has unfair die. How would you actually find out if the die is weighted unequally?

Conducting a Probability Simulation The Steps in a Simulation That Uses Random Digits 1.Assumptions. State the assumptions you are making about how the real-life situation works. Include any doubts you might have about the validity of your assumptions. 2. Model. Describe how you will use random digits to conduct one run of a simulation of the situation. Make a table that shows how you will assign a digit (or a group of digits) to represent each possible outcome. (You can disregard some digits.) Explain how you will use the digits to model the real- life situation. Tell what constitutes a single run and what summary statistic you will record. 3. Repetition. Run the simulation a large number of times, recording the results in a frequency table. You can stop when the distribution doesn’t change to any significant degree when new results are included. 4. Conclusion. Write a conclusion in the context of the situation. Be sure to say that you have an estimated probability

Westvaco Example pg 302 The ages of the ten hourly workers involved in Round 2 of the layoffs were 25, 33, 35, 38, 48, 55, 55, 55, 56, and 64. The ages of the three workers who were laid off were 55, 55, and 64, with average age 58. Use simulation with random digits to estimate the probability that three workers selected at random for layoff would have an average age of 58 or more. Assumptions

Westvaco Simulation Continued… Model:

Repetition with Random Number Generator Work with a partner. Use the random number generator to select 3 workers, find their average age write it down. Complete this simulation 5 times. Record your results on the classroom dotplot.

Using a Random # Table

Homework 5.1 P#8, 9, E#4, 8 and 9 Read 5.2 and 5.3