DSCI 551: Descriptive Statistics and Probability for Data Science
Fundamental concepts in probability. Describing data generated from a probability distribution. Statistical view of data coming from a probability distribution.
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Schedule
| Lecture | Topic | Variable | Dimension |
|---|---|---|---|
| Lecture 1 | discrete | univariate | |
| Lecture 2 | Parametric families | discrete | univariate |
| Lecture 3 | Simulation | discrete | univariate |
| Lecture 4 | Joint probability, Part I | discrete | bivariate |
| Lecture 5 | Continuous distributions | continuous | univariate |
| Lecture 6 | Joint probability, Part II | continuous | bivariate |
| Lecture 7 | Dependence | continuous | bivariate/multivariate |
| Lecture 8 | Noteworthy Distribution Families | continuous | bivariate/multivariate |
Deliverables
You are responsible for the following deliverables, which will determine your course grade:
| Assessment | Weight |
|---|---|
| Lab Assignment 1 | 15% |
| Lab Assignment 2 | 15% |
| Lab Assignment 3 | 15% |
| Lab Assignment 4 | 15% |
| Quiz 1 | 20% |
| Quiz 2 | 20% |
Resources
- JBstatistics (also on YouTube)
- Seeing Theory
- Introduction to Probability, Statistics, and Random Processes
- Harvard STAT 110 course plus YouTube videos
- Probability Cheatsheet and another one
Note: some of these resources cover much more material than DSCI 551.