From the course: Statistics Foundations 3: Using Data Sets
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Random samples
From the course: Statistics Foundations 3: Using Data Sets
Random samples
- Typically, we can't gather the data for an entire population. It's either too expensive, too time consuming, or it's just not possible. So ideally, statisticians look to gather data from parts of the population, a sample of the population. And the most dependable data comes from what's called a simple random sample. In a simple, random sample, each individual in the population has the same probability of being chosen for inclusion in the sample as any other individual. Or each subset of K individuals has the same probability of being chosen for the sample as any other subset of K individuals. For example, in a town of 10,000 people, any 100 people in the town are just as likely to be chosen for inclusion in the sample as any other 100 people in the same town. But gathering a simple random sample is not that simple. Actually, it's quite difficult. Why, well, a simple random sample must exhibit two key characteristics.…
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