These ‘sample mean returns’ can be plotted as a sampling distribution of the mean. All the sample mean returns are an estimate of the population mean. We can draw many such samples of 50 stocks and calculate sample mean returns for each random sample. The ‘ sample mean returns’ is a sample statistic. We can draw random samples of 50 stocks from the population and calculate their mean returns. Let’s say we are looking at a population of 500 stocks. An example of a sample statistic is the mean of sample data.Ī sampling distribution of the mean is the probability distribution of sample mean obtained by drawing all possible samples of the same size from the same population. Sampling DistributionĪ sampling distribution is a probability distribution of the sample statistic. A problem with this method is that the sample may not be a good representative of the population as it may not evenly capture all dimensions of the population. This method of sampling is useful where the population is small. Using a random number algorithm (a computer based random number generator or some other method of generating random numbers) select n units from the list of N units one at a time without replacing the items. We have given an identification number (1 to N) to each item in the population. Simple random sampling is a type of sampling method, in which each element of the population has an equal chance of being selected in the sample.Ī simple random sample can be selected as follows: List all the items in the population say from 1 to N, where N is the total number of items in the population.
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