MKTG 3258 Lecture Notes - Lecture 21: Confidence Interval, Sample Size Determination, Standard Score
8 Feb 2020
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Why samples are acceptable in research: sampling is considered statistically sound, a census in expensive and time consuming, fewer opportunities for errors and biases to impact data. It may be impossible to find an accurate and up to date sample frame for a full census. Computing sample size: a computation of sample size requires three variables, required degree of precision/margin of error, desired level of confidence, estimate of population variability or population size. Precision or margin of error: how much are you willing to be wrong by, what"s the largest gap between obtained result and true result that you can tolerate, ex. Confidence intervals: how often (%) you would get the same results if the study were run over and over again. In the statistical sense, i. e. , a 95% confidence level: or a 90% or a 99%, to use the most common values. Precision" means precision at a given confidence level".
