Subject to revision (last updated: Feb 17, 2022)
Course description
This is an applied course that builds upon knowledge acquired from lower-division statistics coursework. It exposes students to the research and data analysis practices executed in the business world. A focus of this course is on generating reproducible analyses using the R programming language.
Prerequisites
- Pre-business requirements
- Proficiency in spreadsheet software
Learning objectives
- Determine question want to answer with data analysis
- Extract, transform and load relevant data (ETL process)
- Apply appropriate data analytic methods
- Interpret and present the results
Course materials
- R/RStudio
- Course site: stanny.moodle.school. If you are enrolled in the course, I will send you login information.
- If you have any questions about the site, please ask me.
- Videos, notes, quizzes and other materials are posted on the site.
Schedule
| Feb 1 |
1: Introduction/R/RStudio |
due at 5 PM |
| Feb 8 |
2: Install R/RStudio and create a blog |
due at 5 PM |
| Feb 15 |
3: Data manipulation / descriptive analysis I |
due at 5 PM |
| Feb 22 |
4: Reading and writing data |
due at 5 PM |
| Mar 1 |
5: Data manipulation / descriptive analysis II |
due at 5 PM |
| Mar 8 |
6: Data manipulation / joining data |
due at 5 PM |
| Mar 15 |
7: Exploratory analysis / data visualization I |
due at 5 PM |
| Mar 29 |
8: Exploratory analysis / data visualization II |
due at 5 PM |
| Apr 5 |
9: Data visualization / storytelling |
due at 5 PM |
| Apr 12 |
10: Machine learning |
due at 5 PM |
| Apr 19 |
11: Inference / sampling |
due at 5 PM |
| Apr 26 |
12: Inference / bootstrapping |
due at 5 PM |
| May 3 |
13: Inference / hypothesis testing |
due at 5 PM |
| May 10 |
14: Assignment |
due at 5 PM |
| May 17 |
15: Assignment |
due at 5 PM |
Grading
There are 1050 possible points in the course (50 are extra credit points). Your grade will be determined by your total points:
| A |
950 |
| A- |
900 |
| B+ |
870 |
| B |
830 |
| B- |
800 |
| C+ |
770 |
| C |
730 |
| C- |
700 |
| D+ |
670 |
| D |
600 |
Late submissions will not be accepted. Please do not ask.
Policies
- You must adhere to SSU’s Cheating and Plagiarism policy. Academic dishonesty (e.g., cheating, plagiarism, etc.) will not be tolerated and will result in a zero grade (i.e., no points) on the quiz or exam and, possibly, a failing grade in the course.
- Please be advised that the on-line software allows me to track every click you make on the course site. I know whether, when and where you attempt quizzes, access notes, etc.
- There are no opportunities for points not listed above. Please do not ask.
- Disability Services for Students (DSS)
- Academic Accommodation: If you are a student with a disability, and think you may need academic accommodations, please contact Disability Services for Students (DSS), located in Salazar Hall, Room 1049, Voice: (707) 664-2677, TTY/TDD: (707) 664-2958, as early as possible in order to avoid a delay in receiving accommodation services. Use of DSS services, including testing accommodations, requires prior authorization by DSS in compliance with university policies and procedures.
- Students may not record (audio or video) in this class except in accordance with ADA accommodations. Any recordings made in connection with a disability accommodation are for the student’s personal academic use only and may not be distributed in any manner to any other individual.