With billions of users, the internet seems to be a very convenient and useful way to gather information. However, polls on the internet are very susceptible to bias. Internet polls can appeal to different demographics dependent on the question asked. In conjunction, the location of the poll can also determine the demographic. Both undercoverage and
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Pseudo-Random Number Generators (PRNGs) As the word ‘pseudo’ suggests, pseudo-random numbers are not random in the way you might expect, at least not if you're used to dice rolls or lottery tickets. Essentially, PRNGs are algorithms that use mathematical formulae or simply precalculated tables to produce sequences of numbers that appear random. A good example of a PRNG is the linear congruential method. A good deal of research has gone into pseudo-random number theory, and modern algorithms for
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Sampling Designs • 1. Simple random sampling (SRS) Steps: – (1) Assign a single number to each element in the sampling frame. – (2) Use random numbers to select elements into the sample until the desired number of cases is obtained. • The method is not very different from winning a lottery. 2. Systematic Sampling • Steps: – (1) Calculate the sampling interval as the ratio between population size and sample size, I = N/n. – (2) Arrange all elements in the population in an order. – (3) Select
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about it again. Most companies that have a drug testing policy will use random drug tests. Although they have these drug testing policies, only a small number actually give the tests. Out of the companies that conduct random drug tests, their frequency of testing are all different. Some use independent companies to do their testing for them. Although this can be expensive, it’s usually best for companies that do random testing. Employees won’t feel like someone within the company is “out to
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Statistics provides Hr managers with more confidence in dealing with uncertainty in spite of the flood of available data, enabling managers to more quickly make smarter decisions and provide more stable leadership to staff relying on them. Businesses are increasingly using Statistical techniques to convert data into information. Tools and techniques of Statistics are being widely used in HR in many domains that include Compensation survey, Performance Management, Employee Satisfaction Survey, Training
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Cluster Sampling- Cluster sampling takes the population and splits them into random groups which are called clusters. Depending on how many people are needed the researcher will choose a couple of random clusters to use in the research. Cluster sampling is used when it is close to impossible to get info of all the population that is trying to be sampled. For example it would be appropriate to use it if you were trying to get a survey on America's grocery stores. You would find all the stores and
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diverge very little. With a good laser an object at a distance of 1 km (0.6 mile) can be illuminated with a dot about 60 mm (2.3 inches) in radius. As it is so parallel it can also be focused to very small diameters where the concentration of light energy becomes so great that you can cut, drill or turn with the beam. It also makes it possible to illuminate and examine very tiny details. It is this property that is used in surgical appliances and in CD players. It can also be made very monochromic
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studied "fluid" consisting of hard disks. In the nineteenth and early twentieth centuries, statistical problems were sometimes solved with the help of random selections, that is, in fact, by the MC method. Prior to the appearance of electronic computers, this method was not widely applicable since the simulation of random quantities by hand is a very laborious process. Thus, the beginning of the MC method as a highly universal numerical technique became possible only with the appearance of computers
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Solutions to Practice Problems for Part IV 1. Five inspectors are employed to check the quality of components produced on an assembly line. For each inspector, the number of components that can be checked in a shift can be represented by a random variable with mean 120 and standard deviation 16. Let X represent the number of components checked by an inspector in a shift. Then the total number checked is 5X, which has mean 600 and standard deviation 80. What is wrong with this argument? Assuming
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conclusions from data. Students are exposed to four broad conceptual themes: • Exploring Data: Describing patterns and departures from patterns • Sampling and Experimentation: Planning and conducting a study • Anticipating Patterns: Exploring random phenomena using probability and simulation • Statistical Inference: Estimating population parameters and testing hypotheses Students who successfully complete the course and examination may receive credit and/or advanced placement for a one-semester
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