PPT-Random Sampling on Big Data: Techniques and Applications

Author : easyho | Published Date : 2020-08-28

Ke Yi Hong Kong University of Science and Technology yikeusthk Random Sampling on Big Data 2 Big Data in one slide The 3 Vs Volume External memory algorithms Distributed

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Random Sampling on Big Data: Techniques and Applications: Transcript


Ke Yi Hong Kong University of Science and Technology yikeusthk Random Sampling on Big Data 2 Big Data in one slide The 3 Vs Volume External memory algorithms Distributed data. 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. Professor William Greene. Stern School of Business. IOMS Department. Department of Economics. Statistics and Data Analysis. Part 10 – The Law of. Large Numbers . and the Central. Basic Terms. Research units – subjects, participants. Population of . interest (all humans?). Accessible . population – those you can actually try to sample. Intended . sample – those you select for participation. 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. 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. Yu Su*, Gagan Agrawal*, . Jonathan Woodring. #. Kary Myers. #. , Joanne Wendelberger. #. , James Ahrens. #. *The Ohio . State University. #. Los . Alamos National . Laboratory. Motivation. Science becomes increasingly data driven;. Richard Peng. M.I.T.. OUtline. Structure preserving sampling. Sampling as a recursive ‘driver’. Sampling the inaccessible. What can sampling preserve?. Random Sampling. Collection of many objects. Researchers studied the effects that improving vision with eyeglasses had on educational outcomes. They identified 2,069 students who could improve their vision with eyeglasses. 750 were not offered eyeglasses and 1,319 were. Of the 1,319 offered eyeglasses, 928 accepted the eyeglasses. Students who received the eyeglasses scored significantly higher in both math and science. What was the treatment in this study?. 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. 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.. Designing experiments. OUTLINE of topics. Avoid obvious problems with:. The question. Sampling. Variables. How to do sampling.. Principles of experimental design.. Data collection. Consider the following 3 research questions:. 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. 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.. Naturalistic Observation. Ecological vs. External vs. Internal Validity. Observational Studies. Case Study. N = 1. Patient KC: suffered brain damage in accident . Complete damage to episodic memory.

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