PPT-Ch 6: Basic Elements of Sampling

brian schnick BASIC CONCEPTS IN SAMPLING Advantages of Sampling Sampling Error Sampling Procedure Advantages of Sampling Sampling is a necessity in many geographic research problems Population may be simply too big for 100 contact. Husheng Li. The University of Tennessee. Chopper Sampling . We introduce a switching function such that . x_s. (t)=x(t)s(t), where. Nyquist. Criterion. The sampling rate should be at least twice the bandwidth of the signal, in order to fully reconstruct the signal.. 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. How to run these simulations using Amber. vs.. Cazuela. sampling?. (progress of) reaction coordinate. ΔG. (progress of) reaction coordinate. ΔG. Add “restraint” to force simulation. to sample barrier region.. 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.. J. D. Johnston. Factotum. An . Audio Company. THERE IS ONE RULE IN THIS TALK. If you don’t get what’s going on:. ASK A QUESTION!. DO NOT WAIT. But first, a word from our sponsor, the Shannon Sampling Theorem. , Identification and Testing. (S.I.T.) . Introduction. Define basic principles for applying sampling, identification and testing requirements. 1) . Systems and procedures. ensuring that samples are representative of the batch when sampled. x(t. ). x~(t. ). Sound is audible in 20 Hz to 20 kHz range:. . f. max. = 20 kHz and the Nyquist rate 2 . f. max. = 40 kHz . What is the extra 10% of the bandwidth used?. Rolloff. from passband to stopband in the magnitude response of the anti-aliasing filter. Approximately 1050 samples taken annually. Programme prepared in April targeting particular premises and food types. All samples taken informally unless a previous sample was “unacceptable/potentially hazardous” or during an outbreak investigation. Parameter & Statistic. Parameter. Summary measure about population. Sample Statistic. Summary measure about sample. P. . in. . P. opulation. . &. . P. arameter. S. . in. . S. ample. . FOR . AGRICULTURAL STATISTICS. Module 2 - Session . 5:. Using . a Multiple Sampling Frame as an MSF. Objectives of the presentation. Review the . principles of multiple frame . sampling. Deal . with . A new sampling method. Motivating example. Want to study the average amount of water used per person per month. How would you design a survey?. 2. A new sampling method. Consider the two strategies. Sample person by person. 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.. Evangelism Series. Lamb of God. Wellington Branch. Introduction. Evangelism Series: Series of 3 Talks:. Why Evangelise?. How to share your Personal . T. estimony. How to share the Basic Gospel Presentation. Ke. Yi. Hong Kong University of Science and Technology. yike@ust.hk. Random Sampling on Big Data. 2. “Big Data” in one slide. The 3 V’s. : . Volume. External memory algorithms. Distributed data.