From f9cd16d0dec2c39b8cd737fdcdb5b2342f23be7b Mon Sep 17 00:00:00 2001 From: "Steven G. Johnson" Date: Mon, 13 Mar 2023 16:27:06 -0400 Subject: [PATCH] whoops --- psets/pset3.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/psets/pset3.ipynb b/psets/pset3.ipynb index a111e53..af682d7 100644 --- a/psets/pset3.ipynb +++ b/psets/pset3.ipynb @@ -177,7 +177,7 @@ "source": [ "## Problem 7 (5+5 points)\n", "\n", - "The most common form of least-squares is linear regression, i.e. fitting $m$ data points $(a_i, b_i)$ to a model of the form $a(b) = x_1 + b x_2$.\n", + "The most common form of least-squares is linear regression, i.e. fitting $m$ data points $(a_i, b_i)$ to a model of the form $b(a) = x_1 + a x_2$.\n", "\n", "Suppose the data points $b_i$ have independent random errors with equal variances $\\sigma^2$ (i.e. they are \"homoscedastic\"). (This is the case in which Gauss–Markov says that ordinary least-squares minimizes the variance.) In this case, many sources give simple explicit formulas for the variances of the fit coefficients $x_1$ and $x_2$\n", "\n",