Couse: UCSD MATH 189
Quarter: Winter 2023
Instructor: Wenxin Zhou
MATH 189: Exploratory Data Analysis and Inference (4 units)
An introduction to various quantitative methods and statistical techniques for analyzing data—in particular big data. Quick review of probability continuing to topics of how to process, analyze, and visualize data using statistical language R. Further topics include basic inference, sampling, hypothesis testing, bootstrap methods, and regression and diagnostics. Offers conceptual explanation of techniques, along with opportunities to examine, implement, and practice them in real and simulated data. Prerequisites: MATH 18 or MATH 20F or MATH 31AH, and MATH 20C and one of BENG 134, CSE 103, ECE 109, ECON 120A, MAE 108, MATH 180A, MATH 183, MATH 186, or SE 125.
All Homeworks is done by group of 3 people.
| Folder | Requirement | GitHub Link | Feedback | Score | |
|---|---|---|---|---|---|
| HW 1 | HW1 | Requirement | [GitHub] | -- | 40/40 |
| HW 2 | HW2 | Requirement | [GitHub] | Question 2.3: incorrect multiple testing with Bonferroni correction(−3.5 pts) | 36.5/40 |
| HW 3 | HW3 | Requirement | [GitHub] | -- | 25/25 |
| HW 4 | HW4 | Requirement | [GitHub] | -- | 40/40 |
| HW 5 | HW5 | Requirement | [GitHub] | -- | -- |
| HW 6 | HW6 | Requirement | [GitHub] | -- | -- |
| Subject | Slides | |
|---|---|---|
| Lecture 1 | Warm-up: Matrix Algebra | Matrix Algebra_1 Matrix Algebra_2 |
| Lecture 2 | Data Analysis & Inference | Data Analysis |
| Lecture 3 | Descriptive | Descriptive |
| Lecture 4 | Inference for the Mean: Preliminaries | Preliminaries |
| Lecture 5 | Multiple Testing: FWER and FDR | Multiple Testing: FWER and FDR |
| Lecture 6 | Global Mean Testing and Two-Sample Problems | Global Testing |
| Lecture 7 | Multivariate Analysis of Variance | ANOVA |
| Lecture 8 | Classification via Linear Discriminant Analysis | LDA |
| Lecture 9 | Multivariate Linear Regression | LR |
| Lecture 10 | Multivariate Linear Regression | -- |
| Lecture 11 | Classification via Logistic Regression | LogisticReg |
| Lecture 12 | Principal Component Analysis | Principal Component Analysis |
| Lecture 13 |