Class Notes

• Day 1
  • Who is in this class? An investigation
• Day 2:
  • Remember to talk quickly about Options for those with CSCI and STAT experience.
  • Email discussion and notes.
  • Inserting a screen clipping in word.
  • There is a new homework, how will you find it?
• Day 3:
  • What is Data Science? discussion
• Day 4
  • Moore's Law excel activity.
• Day 5/6
  • Super Heroes Dataset activity and project overview.
• A note on the first test
  • The syllabus said that the approximate date will be Oct 3-4
  • I want to postpone this until Oct 10/11
  • The test will include:
    • terms, a glossary will be coming soon.
      • What is data?
      • What is information?
    • Short answers questions
      • What are the advantages of using document level formatting in word?
      • What is the purpose of the BCC field in an email message?
      • Name three areas of expertise a data scientist needs.
      • Why should you use tools to accomplish a task in excel rather than performing that task by hand?
    • Practical skills
      • Divide a word document into three different logical sections.
      • Given a dataset, find all of the terms in a column.
      • Count the number of times a word occurs in a column.
  • You may use your book, and notes, including on line notes.
• Day 7
  • The Height Field.
• Day 8
  • Finishing the Proposal, Part I.
• Day 9
  • Finishing the Proposal, Part II.
• Day 10
  • Page Numbers and Other Things
• Day 11 (Day 12 MW)
  • Formulas and Functions.
• Day 12 (Day 11 MW)
  • Test Review/Work Day
• Day 13
  • Test 1.
• Day 14: (Wk 8)
  • Midterm Grades
  • Computing Grades
• Day 15:
  • Starting a Second Project
• Day 16: (Wk 9)
  • The homework field
• Day 17:
  • Cleaning and exploring the data
• Day 18: (Wk 10)
  • Database Functions (Tables)
  • vlookup intro
• Day 19:
  • vlookup application
• Day 20: (Wk 11)
  • String functions
• Day 21:
  • Date functions, basic pivot tables
• Day 22: (Wk 12) Powerpoint
  • Review Notes
• Day 23: Test 2
• Day 24: (Wk 13)
  • Work Day (Last day before project due)
  • Notes and Example Documents
• Day 25: (Wk 14)
  • Jobs in Data Science
• Day 26:
  • Ethics
• Day 27: (Wk 15) Student Presentations
• Day 28: Student Presentations
• Day 29: (Final Period) Student Presentations.
  • The Schedule

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)