PROBABILITY REVIEW PART 5 PROBABILITY FOR TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.

Slides:



Advertisements
Similar presentations
Homework Answers 9) 6/24 + 6/24 = 12/24 or ½ 11) 12/ /24 = 24/24 or 1 23) P(2 and A) = (1/6 * 1/5) = 1/30 P(2 and B) = (1/6 * 1/5) = 1/30 P(2 and.
Advertisements

EXAMPLE 1 Construct a probability distribution
Copyright © 2011 Pearson, Inc. 9.3 Probability. Copyright © 2011 Pearson, Inc. Slide What you’ll learn about Sample Spaces and Probability Functions.
Working with Random Variables. What is a Random Variable? A random variable is a variable that has a numerical value which arises by chance (ie – from.
Monopoly Game Example Mutually Exclusive.
PROBABILITY  A fair six-sided die is rolled. What is the probability that the result is even?
Probabilistic and Statistical Techniques 1 Lecture 9 Dr. Nader Okasha.
EXAMPLE 1 Construct a probability distribution Let X be a random variable that represents the sum when two six-sided dice are rolled. Make a table and.
MA 102 Statistical Controversies Monday, April 1, 2002 Today: Randomness and probability Probability models and rules Reading (for Wednesday): Chapter.
The Practice of Statistics, Fourth Edition.
PROBABILITY REVIEW PART 9 CONDITIONAL PROBABILITY II Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION THEORY BAYESIAN STATISTICS I Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION THEORY BAYESIAN STATISTICS II Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
PROBABILITY REVIEW PART 4 PROBABILITY FOR TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
TEXT CATEGORIZATION THE FEDERALIST – PART 1 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 3 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 2 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
AP STATISTICS.   Theoretical: true mathematical probability  Empirical: the relative frequency with which an event occurs in a given experiment  Subjective:
COURSE OVERVIEW ADVANCED TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION RETRIEVAL LINEAR ALGEBRA REVIEW Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
MA-250 Probability and Statistics Nazar Khan PUCIT Lecture 10.
TEXT CATEGORIZATION THE FEDERALIST – PART 3 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
Probability of 2 Independent Events Example – Two Independent Events.
INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 1 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 5 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
Chapter 9 Introducing Probability - A bridge from Descriptive Statistics to Inferential Statistics.
INFORMATION THEORY CONDITIONAL ENTROPY Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
INFORMATION THEORY SIMPLIFIED POLYNESIAN LANGUAGE EXAMPLE Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
PROBABILITY REVIEW PART 2 PROBABILITY FOR TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
Simple Mathematical Facts for Lecture 1. Conditional Probabilities Given an event has occurred, the conditional probability that another event occurs.
Statistical Experiment A statistical experiment or observation is any process by which an measurements are obtained.
4.1 Probability Distributions. Do you remember? Relative Frequency Histogram.
1 Discrete Structures – CNS2300 Text Discrete Mathematics and Its Applications (5 th Edition) Kenneth H. Rosen Chapter 5 Counting.
Probability. Sample Spaces and Probability Functions Determining Probabilities Venn Diagrams and Tree Diagrams Conditional Probability Binomial Distributions.
Introduction to Probability © Christine Crisp “Teach A Level Maths” Statistics 1.
Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 5.2: Recap on Probability Theory Jürgen Sturm Technische Universität.
CALCULATE THE PROBABILITY OF AN EVENT. 1.ANSWER THIS QUESTION: IS THE EVENT POSSIBLE? STOP: DON’T CONTINUE. THE PROBABILITY OF THE EVENT IS O GO TO NUMBER.
EXAMPLE 4 Find probabilities of complements Dice When two six-sided dice are rolled, there are 36 possible outcomes, as shown. Find the probability of.
Probability Refresher COMP5416 Advanced Network Technologies.
Essential Statistics Chapter 91 Introducing Probability.
INFORMATION THEORY POLYNESIAN REVISITED Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.
STATISTICS 5.0 Introduction to Probability “Basic Probability Theory” 5.0 Introduction to Probability “Basic Probability Theory” STATISTICS “Basic Probability.
Lesson #35 Outcomes and Probability. Probability is used in….
AP STATISTICS Section 7.1 Random Variables. Objective: To be able to recognize discrete and continuous random variables and calculate probabilities using.
Probability theory is the branch of mathematics concerned with analysis of random phenomena. (Encyclopedia Britannica) An experiment: is any action, process.
Ch. 26 Tests of significance Example: –Goal: Decide if a die is fair. –Procedure: Roll a die 100 times and count the number of dots. We observe 368 total.
1 Discrete Structures - CSIS2070 Text Discrete Mathematics and Its Applications Kenneth H. Rosen Chapter 4 Counting.
STATISTICS 6.0 Conditional Probabilities “Conditional Probabilities”
Probability How likely it is that something will happen.
Probability and Simulation The Study of Randomness.
ROLL A PAIR OF DICE AND ADD THE NUMBERS Possible Outcomes: There are 6 x 6 = 36 equally likely.
Counting and Probability. Imagine tossing two coins and observing whether 0, 1, or 2 heads are obtained. Below are the results after 50 tosses Tossing.
Probability Models Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Continuous Probability Models The Mean and Standard.
Statistics 300: Introduction to Probability and Statistics
Statistics 1: Elementary Statistics
©G Dear 2009 – Not to be sold/Free to use
Suppose you roll two dice, and let X be sum of the dice. Then X is
Experimental vs. Theoretical Probability
7.1 Experiments, Sample Spaces, & Events
Binomial Distributions
E370 Statistical analysis for bus & econ
Statistics 1: Elementary Statistics
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)
Lecture 23 Section Mon, Oct 25, 2004
Uniform Distributions and Random Variables
Modeling Discrete Variables
POPULATION (of “units”)
Essential Statistics Introducing Probability
Calculating Probabilities
Figure 8.1 A pair of dice. Figure 8.1. Figure 8.1 A pair of dice. Figure 8.1.
Presentation transcript:

PROBABILITY REVIEW PART 5 PROBABILITY FOR TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics

Joint (Intersection) Probabilities Joint Probability 2

Joint Probabilities 3 BABA Total 11/64 1/8 21/64 1/8 31/64 1/8 41/64 1/8 51/64 1/8 61/64 1/8 71/64 1/8 81/64 1/8 Total1/8 1 Probabilities from Rolling Two Eight-sided Dice

Joint Probabilities 4 BABA Total 11/64 1/8 21/64 1/8 31/64 1/8 41/64 1/8 51/64 1/8 61/64 1/8 71/64 1/8 81/64 1/8 Total1/8 1 Probabilities from Rolling Two Eight-sided Dice Marginal Probabilities

Joint Probabilities 5 BABA Sum of Pips from Rolling Two Eight-sided Dice

Joint Probabilities 6 BABA Sum of Pips from Rolling Two Eight-sided Dice

7 EventsFace Value Sum

Outcome Count Histogram 8

Event Probability Histogram 9

Probabilities of a Loaded Die 10 OutcomeProbability {1}1/8 {2}1/16 {3}1/8 {4}1/16 {5}1/8 {6}1/16 {7}3/8 {8}1/16

Joint Probabilities of Loaded Dice 11 BABA Total 11/641/1281/641/1281/641/1283/641/1281/8 21/1281/2561/1281/2561/1281/2563/1281/2561/16 31/641/1281/641/1281/641/1283/641/1281/8 41/1281/2561/1281/2561/1281/2563/1281/2561/16 51/641/1281/641/1281/641/1283/641/1281/8 61/1281/2561/1281/2561/1281/2563/1281/2561/16 73/643/1281/643/1281/643/1289/643/1283/8 81/1281/2561/1281/2561/1281/643/1281/2561/16 Total1/81/161/81/161/81/163/81/161 Probabilities from Rolling Two Loaded Eight-sided Dice

Event Probability Histogram 12

References 13 Sources: Foundations of Statistical Natural Language Processing, by Christopher Manning and Hinrich Schütze The MIT Press Discrete Mathematics with Applications, by Susanna S. Epp Brooks/Cole, Cengage Learning

The end has come. End of Probability Slides Part 5 14