Read to yourself David Stenbill Monica Bigoutski Shana Tirana.

Slides:



Advertisements
Similar presentations
SAMPLING DISTRIBUTIONS Chapter How Likely Are the Possible Values of a Statistic? The Sampling Distribution.
Advertisements

Probability Distributions CSLU 2850.Lo1 Spring 2008 Cameron McInally Fordham University May contain work from the Creative Commons.
Chapter 17 STA 200 Summer I Flipping Coins If you toss a coin repeatedly, you expect it to come up heads half the time. Suppose you toss a coin.
Business Statistics for Managerial Decision
Probability - 1 Probability statements are about likelihood, NOT determinism Example: You can’t say there is a 100% chance of rain (no possibility of.
PROBABILITY Uses of Probability Reasoning about Probability Three Probability Rules The Binomial Distribution.
Heuristics and Biases. Normative Model Bayes rule tells you how you should reason with probabilities – it is a normative model But do people reason like.
Inductive Reasoning Bayes Rule. Urn problem (1) A B A die throw determines from which urn to select balls. For outcomes 1,2, and 3, balls are picked from.
C82MCP Diploma Statistics School of Psychology University of Nottingham 1 Overview Parameters and Statistics Probabilities The Binomial Probability Test.
PROBABILITY SAMPLING: CONCEPTS AND TERMINOLOGY
Winning Research Strategies for Case Competitors Mark Bodnar
PROBABILITY How is Probability Useful? Making Probability Judgments. How Are Probabilities Determined?
Statistical inference Population - collection of all subjects or objects of interest (not necessarily people) Sample - subset of the population used to.
PROBABILITY SAMPLING: CONCEPTS AND TERMINOLOGY
Making Decisions in Uncertain Times—Economics You Can Use Capt Kelly Padden, PhD Eaker Center for Professional Development Air University, Maxwell AFB.
Probability and the Sampling Distribution Quantitative Methods in HPELS 440:210.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly source: fivethirtyeight.com.
Multiple Choice Questions for discussion
Chapter 1 Basics of Probability.
P. STATISTICS LESSON 7.2 ( DAY 2)
Chapter 7: The Normal Probability Distribution
AP STATISTICS “Do Cell Phones Distract Drivers?”.
Experiments & Statistics. Experiment Design Playtesting Experiments don’t have to be “big”--many game design experiments take only 30 minutes to design.
Inference for a Single Population Proportion (p).
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
Binomial distribution Nutan S. Mishra Department of Mathematics and Statistics University of South Alabama.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
Poisson Random Variable Provides model for data that represent the number of occurrences of a specified event in a given unit of time X represents the.
Random Sampling, Point Estimation and Maximum Likelihood.
Introduction to Probability
Individual values of X Frequency How many individuals   Distribution of a population.
Applied Business Forecasting and Regression Analysis Review lecture 2 Randomness and Probability.
Maximum Likelihood Estimator of Proportion Let {s 1,s 2,…,s n } be a set of independent outcomes from a Bernoulli experiment with unknown probability.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
Probability Unit 4 - Statistics What is probability? Proportion of times any outcome of any random phenomenon would occur in a very long series of repetitions.
Bayesian vs. frequentist inference frequentist: 1) Deductive hypothesis testing of Popper--ruling out alternative explanations Falsification: can prove.
Math b (Discrete) Random Variables, Binomial Distribution.
LESSON TWO ECONOMIC RATIONALITY Subtopic 10 – Statistical Reasoning Created by The North Carolina School of Science and Math forThe North Carolina School.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
5.1 Randomness  The Language of Probability  Thinking about Randomness  The Uses of Probability 1.
Chapter 7: Sampling Distributions Section 7.1 How Likely Are the Possible Values of a Statistic? The Sampling Distribution.
Randomness, Probability, and Simulation
This is a discrete distribution. Situations that can be modeled with the binomial distribution must have these 4 properties: Only two possible outcomes.
1 7.3 RANDOM VARIABLES When the variables in question are quantitative, they are known as random variables. A random variable, X, is a quantitative variable.
Independent Events Lesson 11-7 Pg. # CA Content Standards Statistics, Data Analysis, and Probability 3.4: I understand that the probability of.
Chapter 8: Probability: The Mathematics of Chance Probability Models and Rules 1 Probability Theory  The mathematical description of randomness.  Companies.
Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly.
Researcher, psychiatrist or interrogator? NICK MUNBY ELTAF Conference
7 th Grade Math Vocabulary Word, Definition, Model Emery Unit 5.
Discrete Probability Distributions Chapter 4. § 4.3 More Discrete Probability Distributions.
AP STATISTICS LESSON THE IDEA OF PROBABILITY.
PH101 lab 1 uncertainty analysis statistics. Sciencing So you have an idea. This idea must be testable... or it is not science So we test it. How good.
Behavioral Finance Economics 437.
Probability Distributions: a review
Chap 6.1 Simulations.
Random Thoughts 2012 (COMP 066)
Probability and Statistics
Perspectives on Peer Review and Enhancing Rigor and Transparency of Scientific Research Michael S Lauer, MD Deputy Director for Extramural Research, National.
The Binomial Distribution
Math Review #3 Jeopardy Random Samples and Populations
Additional notes on random variables
Additional notes on random variables
What do you know about probability?
Section Simulation AP Statistics.
Experimental Probability Versus Theoretical Probability
Experimental Probability Vs. Theoretical Probability
Bernoulli Trials Two Possible Outcomes Trials are independent.
Experimental Probability Vs. Theoretical Probability
Experimental Probability Versus Theoretical Probability
Presentation transcript:

Read to yourself David Stenbill Monica Bigoutski Shana Tirana

Random Thoughts 2012 (COMP 066) Jan-Michael Frahm Jared Heinly (Dense models starting from 3 million images on a single PC in a day)

Last Class Binomial distribution: For events with K successes in N trials Properties of a Binomial distribution: Fixed number of trials Only outcomes are success and fail? Same probability for success in each trial Independent trials (no influence of previous trials to current trial)

Lessons from Reading Assignment The probability that two events will occur can never be greater than the probability that each will occur individually.

Example Linda (p. 22) ordering of probabilities

Is Steve more likely to be a librarian or a farmer? Steve is very shy and withdrawn, invariably helpful but with little interest in people or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail. (Kahneman, “Thinking Fast Thinking Slow”) Is Steve more likely to be a librarian or a farmer? There are more than 20 times the number of male farmers in the US than male librarians. So in all likelihood he will be a farmer. meek and tidy is often resolved

Lessons from Reading Assignment The probability that two events will occur can never be greater than the probability that each will occur individually. “a good story is often less probable than a less satisfying … [explanation]”

Lawyers predict the end of the trial Charges against Bill Clinton by Paula Jones (p. 25-26) how could they tell that the lawyers predict the end more accurately if they split up the different outcomes?

Lessons from Reading Assignment The probability that two events will occur can never be greater than the probability that each will occur individually. “a good story is often less probable than a less satisfying … [explanation]”

Study for cancer in the US A study of the incidence of kidney cancer in 3141 counties of the US reveals a remarkable pattern. The counties in which the incidence of kidney cancer is the lowest are the most rural, sparsely populated and located in traditionally Republican states in the Midwest, the South and the West. The counties in which the incidence of kidney cancer is the highest tend to be the mostly rural, sparsely populated and located in traditionally Republican states in the Midwest, the South and the West. easy and tempting to infer low cancer rates due to clean living (rural live style) easy to infer high cancer due to poverty

Lessons from Reading Assignment The probability that two events will occur can never be greater than the probability that each will occur individually. “a good story is often less probable than a less satisfying … [explanation]” Missing information Availability bias

Words More six letter words ending with ing or with n at the 5th position (p. 28 Moldinov)

Crime Rates What is the average crime rate of Michigan Detroit (highest crime rate in the country) is in Michigan actual crime rate 32.04

Identify Minor celebrities in the triangle Mike Morse Tori Amos Monica Bigoutski Enrique Forrest Lisa Myer Tom Clad Ava Gardner David Stenbill Simon Dunn Tim Kirkman Shana Tirana Joe Zimmerman Rick Dees Ryan Merl Mike Morse Tori Amos Rick Dees Tim Kirkman

Lessons from Reading Assignment The probability that two events will occur can never be greater than the probability that each will occur individually. “a good story is often less probable than a less satisfying … [explanation]” Missing information Availability bias recallable prior knowledge influences our estimates

In Class Discussion Math describes hard facts and is precise Randomness can not be predicted How can we use math to describe random events? not simply say statistics work does a statistic become deterministic if you model precisely and accurately?