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### Basic Statistics for Business and Economics ch 8

What are the reasons for sampling? It would be time consuming. The cost of studying all the items in a population may be prohibitive. The physical impossibility of checking all the items in the population. The destructive nature of some tests. The sample results are adequate.
What are the sampling methods? Simple Random Sample, Systematic Random Sample, Stratified Random Sample, and Cluster Sample.
Simple Random Sample A sample selected sot that each item or person in the population has the same chance of being included.
Table of Random Numbers An efficient way to select members of the sample.
Systematic Random Sample A random starting point is selected, and then every kth member of the population is selected.
Stratified Random Sample A population is divided into subgroups, called stra, and a sample is randomly selected from each stratum.
Cluster Sample A population is divided into clusters using naturally occurring geographic of other boundaries. Then, clusters are randomly selected and a sample is collected by randomly selecting from each cluster.
Sampling Error The difference between a sample statistic and its corresponding population parameter.
Sampling Distribution of the Sample Mean A probability distribution of all possible means of a given sample size.
Central Limit Theorem 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.
Created by: dengler