Description
Respond with at least a 125 words per question. Peer reviewed for references
1 Compare normal distributions with Sampling Distributions.
2 Describe a few different types of sampling, and how to go about identifying the sample; both random and nonrandom sampling.
3 How can provide point and confidence interval estimates in personal and professional settings.
4 Define AND distinguish between normal distributions and sampling distributions. What are some potential examples of each type of distribution from your workplace?
5 Define margin of error and confidence level. How does each affect sample size? What is the recommended sample size for the following populations? What does the relationship between the population and sample size seem to indicate?
a. 200?
b. 2000?
c. 20000?
d. 200000?
6 What is the sample size for 2,000,000? How does this differ for a population of 200,000? What does this mean/what does this tell us about sample size?
NOTE: Use http://www.raosoft.com/samplesize.html to determine the sample size for each (leave margin of error at 5%, confidence level at 95%, and response distribution at 50%).
Explanation & Answer
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Sometimes known as the bell curve, normal distribution of a statistic is the underlying
distribution which occurs naturally. Sampling distribution, on the other hand, is the distribution
of a random variable that is derived from a random sample of size n. The sampling distribution
usually depends on the primary distribution of a population, the sampling procedure used, the
size of the sample and the statistic in consideration. A sample distribution can be drawn from a
normal distribution in which case the distribution is normally distributed over the population
mean and the standard error (Forbes et al). However, the normal distribution is a distribution in a
variate X whose; mean median and mode are all equal; has a symmetrical curve around its mean,
and the number of the value to the left of the mean is equal to the number of values to its...
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