Central to Stats: Sampling!

Introduction to Statistics in Google Sheets

Ted Kwartler

Data Dude

Lesson Overview

• Samples vs populations
• Central Limit Theorem (CLT)

So far, you have...

• Calculated descriptive statistics

So far, you have...

• Calculated descriptive statistics
• Made data visualizations

So far, you have...

• Calculated descriptive statistics
• Made data visualizations
• Used all of the data

So far, you have...

• Calculated descriptive statistics
• Made data visualizations
• Used all of the data
• Worked with "populations"

What is a population?

• An entire distribution of observations/events
• Costly and time consuming to work with
• Better to "sample" the population

Sampling to the rescue

• A subset from a population
• Meant to represent the population
• The larger the sample size, the closer the statistics of the sample will emulate the statistics of the population

• If a sample size from an independent, random variable is large enough, then the sampling distribution will be normal or nearly normal

Central Limit Theorem (CLT)

• "Large enough" is vague...
• How accurate do you need to be? This affects the sample size needed
• The more closely the population follows a normal distribution, the fewer samples will be required
• Minimum number needed is between 30 and 40

Off to do some sampling!

Introduction to Statistics in Google Sheets