STATISTICS FOR ECONOMISTS

What is Statistics for Economists? • The main idea of statistical inference is to take a random sample from a population and then to use the information from the sample to make inferences about particular population characteristics such as the mean (measure of central tendency), the standard deviation (measure of spread) or the proportion of units in the population that have a certain characteristic. • Thus, an important consideration for those planning and interpreting sampling results, is the degree to which sample estimates, such as the sample mean, will agree with the corresponding population characteristic. • A sampling distribution is used to describe the distribution of outcomes that one would observe from replication of a particular sampling plan. • Estimates computed from one sample will be different from estimates that would be computed from another sample. • Estimates are expected to differ from the population characteristics (parameters) that we are trying to estimate, but that the properties of sampling distributions allow us to quantify, probabilistically, how they will differ. • Different statistics have different sampling distributions with distribution shape depending on (a) the specific statistic, (b) the sample size, and (c) the parent distribution. • The variability in a sampling distribution can be reduced by increasing the sample size. • In large samples, many sampling distributions can be approximated with a normal distribution.