Chapter 71.The basis for using a normal probability distribution to approximate the sampling distribution of´and´pis:xa.Chebyshev’s theoremb.The empirical rulec.The central limit theoremd.Bayes’ theorem
2.The standard deviation of´pis referred to as the:
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3.The standard deviation of a point estimator is the :
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4.A simple random sample of sizenfrom a finite population of sizeNis a sample selected such that eachpossible sample of size:
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5.The sampling error is the:a.same as the standard errorb.absolute value of the difference between an unbiased point estimate and the correspondingpopulation parameterc.error caused by selecting a bad sampled.standard deviation multiplied by the sample size
6.Missy Walters owns a mail-order business specializing in baby clothes. Missy is confident the dollaramounts of allher orders are normally distributed or nearly so. Assume she knows the mean andstandard deviation are $249 and $46, respectively, for allorders she receives.a.Describe the sampling distribution of´x, where´xis the mean dollar-amount of an orderfor a sample of 10 orders.b.What is the probability that a simple random sample of 30 orders will provide an estimate of thepopulation mean dollar-amount of an order that is within plus or minus $10 of the actualpopulation mean?
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6. The population being studied is usually considered ______ if it involves an ongoing process that makeslisting or counting every element in the population impossible.a. finiteb. infinitec. skewedd. symmetricANSWER:b
7. A probability sampling method in which we randomly select one of the firstkelements and then selecteverykth element thereafter is _____.c
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8. The standard deviation of a point estimator is the _____.a
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9. The finite correction factor should be used in the computation ofwhenn/Nis greater than_____.c
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10. The set of all elements of interest in a study is _____.a. set notationb. a set ofinterestc. a sampled. a populationANSWER:d
Video Transcript
Hello. So the businesses for using normal probability. Easy. Normal probability. Just attributions. Okay. To approximate. So I probably make the sampling distribution means, okay, the last of the sample. This, uh, the second trial limit. See you already. Okay, so remember that for so I'm just gonna say that to C. L. T. So to use the central the material. Ruminant sample size. Mm hmm. Should be. Yeah. People too. Mhm. 30. Thank you very much.
Video Transcript
we are given in a question that the basis for using a normal priority distribution to approximate sample distribution of sample means and population means is So for this, let us see the definition of each of the four options. One by one here, we can't use empirical rule because empirical rule is used to anticipate empirical rule is used to anticipate probable outcomes in normal distribution. And here the question is not asking about to anticipate the normal distribution, but it is asking us to approximate the sample distribution. So empirical rule can't be the answer of the question then we have based here um again based here um can't with the answer as based here um is used in case of conditional probability. Now we have central limit. Now central limit your um is the answer for our question. As the central limit theorem states, as a sample size gets larger, the sampling distribution of sample means approach a normal distribution. So the answer for the question is central limit Two of them. Hope you understand it. Thank you.