{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

ec41lecture17

ec41lecture17 - Statistics for Economists Lecture 17 Kata...

This preview shows pages 1–7. Sign up to view the full content.

Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Statistics for Economists Lecture 17 Kata Bognar UCLA December 2, 2010

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Final - Announcement The final exam is cumulative , it covers Chapters 3.6 - 4.3, in addition to all chapters covered by the two midterms and the lecture notes. The final is on Monday, December 6, 3:00pm - 6pm. Students with last names A - LE take the exam in MOORE 100. Students with last names LI - Z take the exam in FRANZ 1178. Photo IDs will checked so please bring your ID . You will have 180 minutes to answer multiple choice and short answer questions. No notes or books are permitted in the exam. You may bring a calculator but no cell phones, laptops, etc. is allowed. No own paper is needed. All answers need to be written on the handed out exam forms. The graded finals can be viewed during appointments with the TAs.
Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Last Lecture z-Test for population mean t-Test for population mean

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Today’s Outline 1 Review
Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Basic Concepts Readings: Chapter 1.1 Concepts: random experiment, outcome space events, union and intersection of events, complements of events probability axioms addition rules, mutually exclusive events exhaustive events Questions: define outcome space and events given a random experiment find probabilities of events identify and give examples of mutually exclusive events identify and give examples of exhaustive events

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Statistics for Economists Lecture 17 Kata Bognar UCLA Probability Discrete Distributions Continuous Distributions Inference Methods of Enumeration Readings: Chapter 1.2 Concepts: multiplication principle factorial permutation, combinations binomial coefficient Questions: use factorial, combination and permutation formulas find probabilities using methods of enumeration
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}