Stats final review chapter 7
Reasons to sample
1. To contact the whole population would be time-consuming.
2. The cost of studying all the items in a population may be prohibitive.
3. The physical impossibility of checking all items in the population.
4. The destructive nature of some tests.
5. The sample results are adequate.
Simple Random Sampling
it's so that each item or person in the population has the same chance of being included.
Systematic random sampling
the items or individuals of the population are arranged in some order. A starting point is selected randomly and then every 𝑘th member of the population is selected for the sample.
Stratified random sampling
a population is divided into groups, called strata, and a sample is randomly selected from each stratum. it guarantees that each group is represented in the sample.
Cluster sampling
a population is divided into clusters using naturally occurring geographic or other boundaries. then, clusters are selected randomly and a sample is collected from each cluster selected randomly.
The 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.
Sampling distribution of the proportion
A proportion is the fraction, ratio, or percent indicating the part of the sample or the population having a particular trait of interest.