# Week 5 — Filling In

This week is primarily for **practice** and **solidifying concepts**.
I'm also going to take a step back and give some more context to some of the things we're talking about.

This week's videos are also in a Panopto playlist.

## Week 5 Quiz

The Week 5 quiz is about material **through the end of Week 4**.
Nothing from this week will be on it, except that things here may clarify some of last week's material for you.

## Assignment 1 Solution

I will post the Assignment 1 solution to Piazza (sorry, I'm not posting it to the entire Internet).

## Glossary Updates

I have extensively updated the course glossary. Please post on Piazza if you have suggested additions!

## Writing Functions

I've used Python *functions* in a few of my example notebooks.
The function notebook talks more about them, how to write them, and how to use them.

## Comparing Distributions

This video describes how to use Q-Q plots to compare data against a distribution.

### Resources

## T-tests

This video discusses the *t*-test in more detail, and the different kinds of *t*-tests that we can run.
It also introduces **degrees of freedom**.

## Python Errors

This video discusses common Python errors and how to read errors.

## Python Libraries

### Resources

- NIST Handbook on quantitative meaures (has info on 1-sample and 2-sample
*t*-tests)

## One Sample Notebook

The One Sample notebook demonstrates how to compute a one-sample *t*-test, and draw a Q-Q plot to compare a distribution with normal.

## Epistemology

In this video, I talk about how the quantitative data science methods we are learning fit into a broader picture of source of knowledge.

## Learning More

## Practice

There are a few things you can do to keep practing the material:

- The HETREC data contains two data sets besides the movie data: Delicious bookmarks and Last.FM listening records. Download this data set and apply some of our exploratory techniques to it.
- Download the SBA data from Week 4's activity and describe the distributions of more of the variables.
- Apply the inference techniques from Week 4 to statistically test the differences you observed in Assignment 1.

## More Examples

Some more examples from my own work (these are *not* all cleaned up to our checklist standards):

- Data summary from book gender paper - shows a number of descriptive things, including a stacked area chart.
- Linkage statistics from book data - shows some matploblib things, and computing data linking statistics.

## Tutorials

The indexing notebook is now up!

## Assignment 2

Assignment 2 is due on **September 27**.