# Overview
```{admonition} HW 3
Available: **Wed Feb 12th** (by Midnight)  
Due: **Mon, Feb 24th** (by Midnight)
```

## Weekly Plan: Regression
```{topic} [📚 Monday Feb 10th](https://classroom.github.com/a/Xfxgaqdi) 
- The General Linear Model and Ordinary-Least-Squares with `numpy`
- Univariate regression with `statsmodels`
```

```{topic} Tuesday Feb 11th 
- HW 2 Review
- Multiple regression with `statsmodels`
```

```{topic} [Wednesday Feb 12th]()  
- Regression review
- Analytic parameter uncertainty and inference
- Resampled uncertainty and inference
```

```{topic} Readings
- Data Analysis: A Model Comparison Approach
  - <a href="/pdfs/DAAMCA_Ch2.pdf"/>Chapter 2: Error & Parameter Estimates </a> <em>(from last week)</em>   
  - <a href="/pdfs/DAAMCA_Ch4.pdf"/>Chapter 4: Statistical Inferences About Parameter Values</a> <em>(from last week)</em>  
  - <a href="/pdfs/DAAMCA_Ch5.pdf"/>Chapter 5: Simple Regression</a>  
- Regression and Other Stories
  - <a href="/pdfs/ROS_Chap3_Math_Prob_Basics.pdf"/>Chapter 3: Math and Probability Basics Review</a>  
  - <a href="/pdfs/ROS_Chap4_Stat_Inference.pdf"/>Chapter 4: Statistical Inference</a>  
  - <a href="/pdfs/ROS_Chap6.pdf"/>Chapter 6: Regression Background</a>  
  - <a href="/pdfs/ROS_Chap8.pdf"/>Chapter 8: Fitting Regression Models</a>  
  - <a href="/pdfs/ROS_Quick_Tips.pdf"/>10 quick tips to improve your regression modeling</a>  
- [The Truth about Linear Regression](/assets/pdfs/TALR_23.pdf)
```