Statistics I

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.

• Introduction:
• Sampling & Estimation: Discover how statisticians make sound judgments with limited data.
• The Central Limit Theorem: Learn about the most important statistical tool of all.
• Data Sampling: Techniques for gathering quality statistical data
• Politics & Polling: Explore one of the most familiar uses of statistics.
• Sampling Methods: Sample some basic methods for collecting good data.
• The Sample Mean: What is a statistic, anyway?
• Bias & Variance: Avoid introducing bias into your samples
• Margin of Error I: Learn how to judge the results of a statistical analysis.
• Margin of Error II: Estimate error without the population variance.
• More on Bias: Become adept at spotting bias.
• Sample Variance: Count degrees of freedom to resolve a common misconception.