220 likes | 520 Views
BA 201. Lecture 6 Basic Probability Concepts. Topics. Basic Probability Concepts Approaches to probability Sample spaces Events and special events Using Contingency Table (Joint Probability Table, Venn Diagram) The multiplication rule The addition rule Conditional probability
E N D
BA 201 Lecture 6 Basic Probability Concepts
Topics • Basic Probability Concepts • Approaches to probability • Sample spaces • Events and special events • Using Contingency Table (Joint Probability Table, Venn Diagram) • The multiplication rule • The addition rule • Conditional probability • The Bayes’ theorem • Statistical Independence
Population and Sample p.?? Population Sample Use statistics to summarize features Use parameters to summarize features Inference on the population from the sample
p.155 Approaches to Probability • Apriori classical probability • Based on prior knowledge of the process involved • E.g. Analyze the scenarios when tossing a fair coin • Empirical classical probability • Based on observed data • E.g. Record the number of heads and tails in repeated trials of tossing a coin • Subjective probability • Based on individual’s past experience, personal opinion and analysis of a particular situation • E.g. Evaluate the status of a coin someone has offered to use to gamble with
p.156 Sample Spaces • Collection of All Possible Outcomes • E.g. All 6 faces of a die: • E.g. All 52 cards of a bridge deck:
p.156 Events • Simple Event • Outcome from a sample space with 1 characteristic • E.g. A Red Card from a deck of cards • Joint Event • Involves 2 outcomes simultaneously • E.g. An Ace which is also a Red Card from a deck of cards
p.159 Special Events Null Event • Impossible Event • Impossible event • E.g. Club & Diamond on 1 card draw • Complement of Event • For event A, all events not in A • Denoted as A’ • E.g. A: Queen of Diamond A’: All cards in a deck that are not Queen of Diamond
p.159 Special Events (continued) • Mutually Exclusive Events • Two events cannot occur together • E.g. A: Queen of Diamond; B: Queen of Club • Events A and B are mutually exclusive • Collectively Exhaustive Events • One of the events must occur • The set of events covers the whole sample space • E.g. A: All the Aces; B: All the Black Cards; C: All the Diamonds; D: All the Hearts • Events A, B, C and D are collectively exhaustive • Events B, C and D are also collectively exhaustive
pp. ??-?? Using Contingency Table (Joint Probability Table, Venn Diagram) 50% of borrowers repaid their student loans. 20% of the borrowers were students who had a college degree and repaid their loans. 25% of the students earned a college degree.
pp. ??-?? Using Contingency Table (Joint Probability Table, Venn Diagram) (continued) Attribute A AttributeB
pp. ??-?? Using Contingency Table (Joint Probability Table, Venn Diagram) (continued) Attribute A AttributeB Total Total Joint probabilities Marginal probabilities
pp. ??-?? Using Contingency Table (Joint Probability Table, Venn Diagram) (continued) What is the probability that a randomly selected borrower will have a college degree or repay the loan? What is the probability that a randomly selected borrower will have a college degree and default on the loan?
pp. ??-?? Using Contingency Table (Joint Probability Table, Venn Diagram) (continued) If you randomly select a borrower and have found out that he/she has defaulted on the loan, what is the probability that he/she has a college degree? If you randomly select a borrower and have found out that he/she does not have a college degree, what is the probability that he/she will default?
p.170 Computing Joint Probability:The Multiplication Rule • The Probability of a Joint Event, A and B:
p.160 Computing Compound Probability: The Addition Rule • Probability of a Compound Event, A or B:
p.166 Conditional Probability • Conditional Probability:
pp. ??-?? Bayes’ Theorem Using Contingency Table 50% of borrowers repaid their loans. Out of those who repaid, 40% had a college degree. 10% of those who defaulted had a college degree. What is the probability that a randomly selected borrow who has a college degree will repay the loan?
pp. ??-?? Bayes’ Theorem Using Contingency Table (continued) Attribute A AttributeB
p.175 Bayes’ Theorem Using the Formula
p.169 Statistical Independence • Events A and B are Independent if • Events A and B are Independent when the Probability of One Event, A, is Not Affected by Another Event, B
Summary • Introduced Basic Probability Concepts • Approaches to probability • Sample spaces • Events and special events • Illustrated Using Contingency Table (Joint Probability Table, Venn Diagram) • The multiplication rule • The addition rule • Conditional probability • The Bayes’ theorem • Discussed Statistical Independence