Stats Durham College
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
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| show | The results of a sample may adequately estimate the value of the population parameter, thus saving time and money
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| show | It may be too time consuming to contact all members of the population
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| show | It may be impossible to check or locate all the members of the population
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| show | The cost of studying all the items in the population may be prohibitive
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| show | Often, testing destroys the sampled item and it cannot be returned to the population
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| show | A sample selected so that each item or person in the population has the same chance of being included
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| Systematic Random Sampling | show 🗑
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| show | A population is divided into subgroups, called strata, and a sample is randomly selected from each stratum
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| show | A population is divided into clusters using naturally occurring geographic or other boundaries. Then, clusters are randomly selected and a sample is collected by randomly selecting from each cluster
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| show | The difference between a sample statistic and its corresponding population parameter
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| Sampling Distribution of the Sample Mean | show 🗑
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| show | If all samples of a particular size are selected from any population, the sampling distribution of the sample mean is approximately a normal distribution. This approximation improves with larger samples
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| show | The fraction, ratio, or percent indicating the part of the sample or the population having a particular trait of interest
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| Sampling Distribution of the Sampling Proportion | show 🗑
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| show | For a given sample size, the mean of all possible sample means selected from a population is equal to the population mean
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| Sampling Distribution of the Sample Mean | show 🗑
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| Sampling Distribution of the Sample Mean | show 🗑
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| Sampling Distribution of the Sample Mean | show 🗑
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| show | Assume the population standard deviation is known. To determine the probability that a sample mean falls in a particular region, use the following formula:
z=x-bar - mu/(stdev/sqrt(n))
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| show | The sampling distribution of the proportion follows a normal distribution if np and n(1-p) >5.
1. The sample proportion is p-bar=x/n
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| show | z=p-bar-p/(sqrt(p(1-p))/n)
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| show | mean of the sampling distribution of the sample mean
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| sigma sub x bar | show 🗑
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| show | estimate of the standard error of the sample mean
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| show | population standard error of the sample proportion
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