1. Distinguish between probability and non-probability sampling and discuss the advantages and disadvantages of each. If you can not specify the probability that any given individual will be in the ...

Central Limit Theorem: A sampling distribution of the mean is approximately normally distributed if the sample size is sufficiently large. This is true no matter what the population distribution is.

Statistics are often estimated from a sample rather than from the entire population. If the inclusion probability of the sample is unknown to the researcher, that is, a nonprobability sample, naively ...

Learn about t-test assumption, including scale, sampling, normality, sample size, and variance equality, for accurate statistical analysis and reliable results.

When particles in a sample are the same size, one particle can be measured to report the result. If the sample has a narrow distribution, such as 10-25 µm, then measurement of just a few particles can ...