- A note on computational resources for this class for this semester.
- What is Data Science?
- Potential sources for data.
- The Proposal paper
- Sorting and Filtering
- Some basic excel
- Simple Statistics
- Analysis of two text fields
- Expectations for basic statistics
- Pivot Tables
- Text to columns and vlookup
- Charts
- Storytelling with Data
- End of the semester plans
- Powerpoint
- The Slideshow from 11/3 (What I expect for the end of the semester and presentation guidelines).
- Some Advanced Counting
- Ethical Considerations

Recordings

- 8/18
- 8/25
- 8/27
- 9/1
- 9/8
- 9/10
- 9/15
- 9/17
- 9/29
- 10/1
- 10/6
- 10/8
- 10/13
- 10/15
- 10/20
- 10/22
- 10/27
- 10/29
- 11/3
- 11/5

A Glossary.

The course outline includes:

- Introduction to Data Science
- Overview of Data Science ✔
- Reproducible Research and the Need for Documentation ✔
- Planning a Data Science Project ✔

- Professional Data Science
- Roles in Data Science
- Ethical Involving Data
- Issues with Prediction and Fairness

- Introduction to Spreadsheet Software
- Cells, Data and Formulas ✔
- Built in Functions ✔
- Multi-sheet Workbooks ✔

- Identifying and Obtaining Data
- Sources for Data ✔
- Web Searching Strategies ✔
- Organizing Data on a Computer
- Importing Data

- Evaluating and Cleaning Data
- Transforming Data ✔
- Dealing with Missing Data ✔

- Analyzing Data
- Basic Statistical Functions ✔
- Sorting and Filtering Data ✔
- Introduction to Tables ✔
- Basic Pivot Tables ✔

- Visualizing Data
- Creating Graphs Using a Spreadsheet ✔
- Types of Graphs ✔
- Properly Documenting and Labeling Graphs ✔

- Presenting Results
- Formatting Written Reports ✔
- Tools for Documenting Sources and References ✔
- Presentation Software ✔
- Sharing Data Between Productivity Products ✔

- Other Tools in Data Science (optional)