PPT-Sampling

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. 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. 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. Lisa g. Johnston. WWW.lisagjohnston.com, lsjohnston.global@gmail.Com. University of California, san Francisco. Tulane university, new Orleans. Outline. Why is RDS superior for sampling . A/YKP?. RDS Overview. Sampling is perhaps the most important step in assuring that good quality aggregates are being used on INDOT contracts. Since a sample is just a small portion of the total material, the importance th 7.1 The Sampling Theorem. 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. ADC Types. EE174 – SJSU. Tan Nguyen. A continuous-time signal . x. (. t. ) with frequencies no higher than . f. max. can be reconstructed from its samples . x. [. n. ] = . x. (. nT. s. ) if the samples are taken at a proper sampling frequency . 7.1 The Sampling Theorem. 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. William Cohen. MORE LDA SPEEDUPS. First - RECAP LDA . DEtails. Called “collapsed Gibbs sampling” since you’ve marginalized away some variables . Fr. : Parameter estimation for text analysis - . 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. YR04 Efforts. MFRPA Alliance and Lab Accreditation Meeting. Louisville, KY February 2, 2016. Overview of . S. ampling Working Group Efforts. Publication of the “Guidance on Obtaining Defensible Samples” (. as your field technicians.. Jeff Martin, Astrea Taylor, . & Nancy Zikmanis. Next Phase of the Project Life Cycle. PLANNING:. . SAMPLING:. . ASSESSMENT:. EVALUATION: . Plan for data collection using the DQO . 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.. EUS 210. Types of Dielectric. Mineral Oil . Polychlorinated biphenyls (PCBs). Silicone-based or Fluorinated Hydrocarbons. Natural and Synthetic Esters. Air. Why Do We Sample the oil. In-Service Electric Transformer:.