From the course: Statistics Foundations 3: Using Data Sets
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Standard error for proportions
From the course: Statistics Foundations 3: Using Data Sets
Standard error for proportions
- Before we dive into standard error, let's recap a few things we already know. In an experiment, we may collect numerous simple random samples. Each sample has a sampling proportion. For example, in a sample of 10 students, eight of 10 students passed the test. 80% is our sampling proportion. Remember, we have numerous simple random samples. When data is normally distributed, we expect 68% of simple random samples collected from the population to fall within one standard deviation of the population proportion. In other words, if the actual population proportion is 70% and one standard deviation is 10%, we would expect 68% of simple random samples to fall between the lower limit of 60% and an upper limit of 80% which brings us to the standard error. The standard error is the standard deviation of our proportion distribution. Let's use an example to calculate the standard error and then tie it back to everything we've…
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