reg exercise

book/regression.ipynb

@@ -2,10 +2,9 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "deec4c08",
    "metadata": {},
    "source": [
-    "(correlation)=\n",
+    "(regression)=\n",
     "# Regression\n",
     "\n",
     "\n",
@@ -24,7 +23,6 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "3c9aa032",
    "metadata": {
     "tags": [
      "remove-input"
@@ -505,7 +503,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8ec6c766",
    "metadata": {},
    "source": [
     "### The Slope\n",
@@ -595,7 +592,6 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "cb03be31",
    "metadata": {
     "tags": [
      "remove-input"
@@ -1021,7 +1017,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7e6c8c5c",
    "metadata": {},
    "source": [
     "### Outliers\n",
@@ -1066,7 +1061,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "64cc25f3",
    "metadata": {},
    "source": [
     "## Regression Fallacy\n",
@@ -1150,7 +1144,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8fa71a4",
    "metadata": {},
    "source": [
     "## Exercises\n",
@@ -1195,7 +1188,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1b68d4ba",
    "metadata": {},
    "source": [
     "## Python\n",
@@ -1208,7 +1200,6 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "7d6da5d1",
    "metadata": {},
    "outputs": [
     {
@@ -1296,7 +1287,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "52a48371",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1305,7 +1295,7 @@
  "metadata": {
   "celltoolbar": "Edit Metadata",
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1319,7 +1309,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,

book/solutions.md

@@ -146,3 +146,17 @@ Let A have an average of 1000 with an SD of 1. Let school B have an average of 1
 ```{solution-end}
 ```
 
+## [Correlation](correlation)
+
+## [Regression](regression)
+
+
+```{solution-start} assortMating
+:class: dropdown
+```
+
+Researchers report both correlations and slopes, indicating that both can be interesting. If you want to know the effect size, use a slope. If you want to measure the strength of the relationship in terms of noisy vs perfectly linear, use a correlation coefficient.
+
+
+```{solution-end}
+```