Class Notes

• Week 1
  • Syllabus
  • Who is in this class? An investigation
  • Email discussion.
• Week 2
  • Inserting a screen clipping into a word document.
  • What is data science?
• Week 3
  • Finish what is data science?
  • Where to find data.
  • Starting a project. (Styles, TOC)
  • Adding Citations and a BIb (References, citations, bib)
• Week 4
  • Cover Page and Sample Data. (Cover Page, basic tables, intro to sections)
  • Setting up the Project Workbook(Worksheets, About worksheet)
  • Page Numbering Part 1(Page Numbers, simple)
• Week 5
  • Page Numbering Part 2(Full Page Numbers)
  • Sorting Data (Sorting, Simple data cleaning)
• Week 6
  • Filtering Data (Filtering, Advanced Filtering)
  • Tables (Tables)
• Week 7
  • Some Notes
  • Excel Overview (data types,functions and formulas)
  • Basic Formulas (formulas, absolute vs relative references)
  • Functions (functions, pmt)
• Week 8
  • The Next Phase of the Project (An overview for the Methods Document)
  • Analyzing the Weight Field (count, counta, countblank, min, max, quartile.*)
• Week 9
  • Finishing the Basic Analysis of a Numeric Field (stdev.*, average, countif, mode, histogram)
  • Summary of expectations for numeric fields
  • Exploring Text Fields
• Week 10
  • Summary of expectations for text fields.
  • Introduction to Pivot Tables
  • More Pivot Tables
  • Text to columns
• Week 11
  • Vlookup
  • More String Manipulation
• Week 12
  • Exploring Charts
  • Powerpoint Overview
• Week 13
  • Guidelines for presentations
  • A look at ethics in data science
• Week 14
  • Employment Prospects
• Week 15/ Finals Week
  • Presentations

1. Introduction to Data Science
   1. Overview of Data Science ✔
   2. Reproducible Research and the Need for Documentation ✔
   3. Planning a Data Science Project ✔
2. Professional Data Science
   1. Roles in Data Science ✔
   2. Ethical Involving Data
   3. Issues with Prediction and Fairness
3. Introduction to Spreadsheet Software
   1. Cells, Data and Formulas ✔
   2. Built in Functions ✔
   3. Multi-sheet Workbooks ✔
4. Identifying and Obtaining Data
   1. Sources for Data ✔
   2. Web Searching Strategies ✔
   3. Organizing Data on a Computer
   4. Importing Data ✔
5. Evaluating and Cleaning Data
   1. Transforming Data ✔
   2. Dealing with Missing Data ✔
6. Analyzing Data
   1. Basic Statistical Functions ✔
   2. Sorting and Filtering Data ✔
   3. Introduction to Tables ✔
   4. Basic Pivot Tables ✔
7. Visualizing Data
   1. Creating Graphs Using a Spreadsheet ✔
   2. Types of Graphs ✔
   3. Properly Documenting and Labeling Graphs ✔
8. Presenting Results
   1. Formatting Written Reports ✔
   2. Tools for Documenting Sources and References ✔
   3. Presentation Software ✔
   4. Sharing Data Between Productivity Products ✔
9. Other Tools in Data Science (optional)