PPT-The Magic of Random Sampling:

Author : min-jolicoeur | Published Date : 2017-11-04

From Surveys to Big D ata Edith Cohen Google Research Tel Aviv University Disclaimer Random sampling is classic and well studied tool with enormous impact across

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "The Magic of Random Sampling:" is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

The Magic of Random Sampling:: Transcript


From Surveys to Big D ata Edith Cohen Google Research Tel Aviv University Disclaimer Random sampling is classic and well studied tool with enormous impact across disciplines This presentation is biased and limited by its length my research interests experience understanding and being a Computer Scientist I will attempt to present some big ideas and selected applications I hope to increase your appreciation of this incredible tool. Last Edit Date 9122014 105739 AM Sunday Monday Tuesday Wednesday Thursday Friday Saturday Walt Disney World Operating Hours October 2014 10514 10614 10714 10814 10914 101014 101114 Magic Kingdom 9am 7pm Magic Kingdom 9am 11pm Magic Kingdom 9am 11 Last Edit Date 10102014 102848 AM Sunday Monday Tuesday Wednesday Thursday Friday Saturday Walt Disney World Operating Hours December 2014 12714 12814 12914 121014 121114 121214 121314 Magic Kingdom 9am 7pm Magic Kingdom 9am 12am Magic Kingdom 9am RAN#. Random Sampling using Ran#. The Ran#: Generates . a pseudo . random number to 3 decimal places that . is less than 1.. i.e. . it generates a random number in the range . [0, 1. ]. . Ran#. . is in Yellow. Sampling . using. RANDOM. Random Sampling using RANDOM. Random: Generates . a pseudo . random number to 3 decimal places that . is less than 1.. i.e. . it generates a random number in the range [0, 1. Table of Contents. Overview of sampling in e-Discovery. Why sample? . Types of sampling. What is “statistically valid” sampling?. Mathematical considerations before sampling. How to sample in document review. and . Introduction to Experimental Design. Simple Random Sample:. n. measurements from a population . Population subset. Selected such that:. Every sample of size . n. from the population has an equal chance of being selected. Richard Peng. M.I.T.. Joint work with . Dehua. Cheng, Yu Cheng, Yan Liu and . Shanghua. . Teng. (U.S.C.). Outline. Gaussian sampling, linear systems, matrix-roots. Sparse factorizations of . L. p. Choosing your participants for your research.. Sample. The group of participants that make up your research. Samples are supposed to represent the . population . that you are researching but the way you choose to find your sample is dependent on many factors.. How do Sociologists choose the participants for their research?. Starter. Think. - Work independently for 2 minutes to write in as many key concepts into the worksheet as you can. . Pair. - Now, work in a pair with the person sitting next to you for 2 minutes and help each other with any key concepts you couldn't do on your own.. SAI India. September 2011. Sampling is used by SAI-India extensively in. Financial Audit. Compliance Audit. Performance Audit. Sampling. Planning. – selection of units for audit. Audit Execution – selection of transactions for detailed scrutiny. Random Sampling using Ran#. The Ran#: Generates . a pseudo . random number to 3 decimal places that . is less than 1.. i.e. . it generates a random number in the range . [0, 1. ]. . Ran#. . is in Yellow. A link between Continuous-time/Discrete-time Systems. x. (. t. ). y. (. t. ). h. (. t. ). x. [. n. ]. y. [. n. ]. h. [. n. ]. Sampling. x. [. n. ]=. x. (. nT. ), . T. : sampling period. x. [. n. ]. x. How . can it be that mathematics, being after all a product of human thought independent of experience, is so admirably adapted to the objects . of reality. Albert Einstein. Some parts of these slides were prepared based on . 7. Introduction. In . a typical statistical inference problem, you want to discover one or more characteristics of a given population. .. However, it is generally difficult or even impossible to contact each member of the population..

Download Document

Here is the link to download the presentation.
"The Magic of Random Sampling:"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.

Related Documents