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.

Prerequisites

• Statistics Fundamentals
• Introduction to Probability