ECO220Y5 Chapter Notes - Chapter 10: Sampling Distribution, Standard Deviation, Normal Distribution
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Say we take many random samples of 1000 people and find the proportion of each sample being male. Let"s collect all those proportions into a histogram. But it"s reasonable to think that it"ll be very close to the true proportion. We"ll likely never know the value of the true proportion, but it"s important so we give it a label (p). A computer can pretend to draw random samples of 1000 people from some population of values over. In this way we can model the process of drawing many samples from a real population. This is a simulation, and it can help us understand how sample proportions vary due to random sampling. The answer is yes, and it"s higher for small samples. Notation p & q for sample vs. population. We use p for the proportion of successes in the population and p for the observed proportion of successes in a sample.
