'Cov x y' presentation slideshows

Information Theory For Data Management

Information Theory For Data Management. Divesh Srivastava Suresh Venkatasubramanian. Motivation. -- Abstruse Goose (177). Information Theory is relevant to all of humanity. Background. Many problems in data management need precise reasoning about information content, transfer and loss

1.74k views • 150 slides

Welcome to BUAD 310

Welcome to BUAD 310. Instructor: Kam Hamidieh Lecture 9, Wednesday February 12, 2013. Agenda & Announcement. Today : (Quick) Demo of StatCrunch on getting normal probabilities (will put our YouTube clip soon.) Finish up from last time, Chapters 10 & 12 Note:

502 views • 32 slides

Bivariate Methods

377 views • 26 slides

Applied Econometrics Maximum Likelihood Estimation and Discrete choice Modelling

Applied Econometrics Maximum Likelihood Estimation and Discrete choice Modelling. Nguyen Ngoc Anh Nguyen Ha Trang. Content. Basic introduction to principle of Maximum Likelihood Estimation Binary choice RUM Extending the binary choice Mutinomial Ordinal. Maximum Likelihood Estimation.

481 views • 25 slides

Welcome to BUAD 310

Welcome to BUAD 310. Instructor: Kam Hamidieh Lecture 10, Wednesday February 19, 2013. Agenda & Announcement. Today : Finish up from last time Parts of Chapters 13 and 14 . Talk about Exam 1 Note: Homework 3 is due tomorrow 8 AM. . Exam 1.

368 views • 23 slides

ENEE 324: Conditional Expectation

ENEE 324: Conditional Expectation. Richard J. La Fall 2004. Conditional Expectation. Example: Toss a coin 3 times X = number of heads in 3 independent tosses Y = length of the longest run of heads Compute. 1/8. 3. 1/4. 2. 3/8. 1/8. 1. 1/8. 3. Conditional Expectation.

562 views • 23 slides

Statistical Inference

Statistical Inference. Most data comes in the form of numbers We have seen methods to describe and summarise patterns in data . Most data are samples (subsets) of the population of interest. Random variables and their probability distributions describe patterns in populations.

544 views • 18 slides

Chapters 7 and 10: Expected Values of Two or More Random Variables

Chapters 7 and 10: Expected Values of Two or More Random Variables. http://blogs.oregonstate.edu/programevaluation/2011/02/18/timely-topic-thinking-carefully/. Covariance. Joint and marginal PMFs of the discrete r.v . X (Girls) and Y (Boys) for family example. Example: Covariance(1).

258 views • 14 slides

Stat 13 Lecture 22 comparing proportions

Stat 13 Lecture 22 comparing proportions. Estimation of population proportion Confidence interval ; hypothesis testing Two independent samples One sample, competitive categories (negative covariance) One sample, non-competitive categories (usually, positive covariance). An Example.

214 views • 7 slides