2. PROBABILITY REVIEW PART 2 PROBABILITY FOR TEXT ANALYTICS Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics

3. Random Experiment  Outcome  Result cannot be predicted  But comes from the sample space

4. Random Variables 3

5. Events

6. Probability Theory

8. Equally Likely Probability Formula

9. Cardinality Notation

10. Probabilities 9  Numbers between 0 and 1 inclusive  Probability Distributions  Probability Functions

11. Probabilities 10

12. Computing Probability 11

13. References 12 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

14. The end has come. End of Probability Slides Part 2 13