Overall objectives

\n", "\n", "After this chapter,\n", "\n", "1. You can fit a regression with `statsmodels` or `sklearn`\n", "2. You can view the results visually or numerically of your model with either method\n", "5. You can measure the goodness of fit on a regression\n", "3. You can interpret the mechanical meaning of the coefficients for\n", " - continuous variables\n", " - categorical a.k.a qualitative variables with two or more values (aka \"dummy\", \"binary\", and \"categorical\" variables\n", " - interaction terms between two X variables \n", " - variables in models with other controls included (including categorical variables)\n", "4. You understand what a t-stat / p-value does and does not tell you\n", "6. You are aware of common regression analysis pitfalls and disasters\n", "\n", "![](https://media.giphy.com/media/yoJC2K6rCzwNY2EngA/giphy.gif)\n" ] } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.13" } }, "nbformat": 4, "nbformat_minor": 4 }