6.2. Learning Objectives

Conceptual

After this week you should be able to:

• Define the sampling distribution of a statistic (such as the sample mean or proportion)
• Define standard error and explain its relationship to standard deviation
• Explain how the standard error depends on sample size n
• State the Central Limit Theorem and know when it applies

• Define a confidence interval
• Calculate a 95% or 99% confidence interval for the mean of a large sample

This material is covered in the lecture and recapped in the worked examples in Python

Python skills

This week there is an emphasis on simulating the process of drawing a large number of samples from a parent distribution

The key skill practiced this week is building a for loop to repeat a process many times (such as drawing a random sample and getting its mean)

You might need to change some variable (such as sample size n) on each pass through the loop.

Additional new(ish) Python skills:

• Plot an expected distribution such as a curve from the function stats.norm.pdf() over a histogram of simulated data
• Plot a Q-Q plot

This material is covered in the Jupyter Notebooks in this section