Sampling
Learn how to create representative samples to reduce bias and draw conclusions about populations.
Sampling & Estimation
The Central Limit Theorem
Politics & Polling
Sampling Methods
The Sample Mean
Margin of Error I
Margin of Error II
More on Bias
Sample Variance
Course description
We make many day-to-day decisions without seeing the big picture. Sometimes things turn out in our favor, sometimes not. Scientists, engineers, and other technically-minded people also make judgments using limited information. However, their fields have exacting standards, so a toolkit for making good conclusions from small data samples is invaluable to them. This course covers the first step in making a sound statistical conclusion: sampling. A representative sample is essential to getting started with statistics, and by the end of this course, you will be able to create a representative sample, reduce bias, and calculate preliminary results. You'll gain hands-on experience with sampling methods, and be able to spot bias from experimental design to sample selection.
Topics covered
- Bias
- Mean comparison
- Proportion comparison
- Sampling
Prerequisites and next steps
The basics of statistics covered in a first semester stats course is crucial. Familiarity with some basic concepts from probability, such as distribution functions, mean, variance, and the central limit theorem, is necessary. Some calculus knowledge will be helpful, but not essential.