diff --git a/lecture_26/.ipynb_checkpoints/lecture_26-checkpoint.ipynb b/lecture_26/.ipynb_checkpoints/lecture_26-checkpoint.ipynb
new file mode 100644
index 0000000..2fd6442
--- /dev/null
+++ b/lecture_26/.ipynb_checkpoints/lecture_26-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lecture_26/compiled_data.csv b/lecture_26/compiled_data.csv
new file mode 100644
index 0000000..ea6a99a
--- /dev/null
+++ b/lecture_26/compiled_data.csv
@@ -0,0 +1,233 @@
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diff --git a/lecture_26/lecture_26.ipynb b/lecture_26/lecture_26.ipynb
new file mode 100644
index 0000000..dc43ec3
--- /dev/null
+++ b/lecture_26/lecture_26.ipynb
@@ -0,0 +1,1060 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "%plot --format svg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "setdefaults"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Monte Carlo Dart Challenge\n",
+ "\n",
+ "\n",
+ "\n",
+ "In homework 2, you created `projectile.m`, that calculated the height of a dart based upon initial velocity and angle. \n",
+ "\n",
+ "For extra credit, we compiled data from 40 students. \n",
+ "\n",
+ "Now, we want to calculate the control that these students had over their dart-throwing. \n",
+ "\n",
+ "This is called an *inverse problem*. Given, a mean and standard deviation of velocity and angle, we can calculate the mean and standard deviation of the final dart height with a Monte-Carlo model, but we want to determine a reasonable estimate for the mean and standard deviation of these two parameters. \n",
+ "\n",
+ "This is an open-ended design problem, so you can choose to fix or vary the parameters at your own discretion. In HW3, we used 15 m/s as an initial velocity. This is a good starting point, but is it fixed? Its up to you to decide. \n",
+ "\n",
+ "You can use the Matlab/Octave command `hist` to plot the data and the Monte Carlo model results. And you can compare statistics with `mean` and `std`\n",
+ "\n",
+ "State your assumptions and provide documentation for your functions and scripts. \n",
+ "\n",
+ "### The goal of this challenge comes down to 3 parts:\n",
+ "\n",
+ "1. Determine a range of values for initial velocity and angle (intuition or analysis)\n",
+ "\n",
+ "2. Describe initial velocity and angle with random variables (normal distribution? completely random?)\n",
+ "\n",
+ "3. Show that your random variables produce the same ditribution of dart locations as our throwers\n",
+ "\n",
+ "### Submit your repository via the Google Form:\n",
+ "[https://goo.gl/forms/MwdfNWgj9UlHnRV83](https://goo.gl/forms/MwdfNWgj9UlHnRV83)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ans = 40\r\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ ""
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "darts=dlmread('compiled_data.csv',',');\n",
+ "x_darts=darts(:,1).*cosd(darts(:,2));\n",
+ "y_darts=darts(:,1).*sind(darts(:,2));\n",
+ "\n",
+ "colormap(colorcube(length(darts(:,3))))\n",
+ "max(darts(:,3))\n",
+ "scatter(x_darts, y_darts, [], darts(:,3))\n",
+ "xlabel('x position (cm)')\n",
+ "ylabel('y position (cm)')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/svg+xml": [
+ ""
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "hist(y_darts)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Octave",
+ "language": "octave",
+ "name": "octave"
+ },
+ "language_info": {
+ "file_extension": ".m",
+ "help_links": [
+ {
+ "text": "MetaKernel Magics",
+ "url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
+ }
+ ],
+ "mimetype": "text/x-octave",
+ "name": "octave",
+ "version": "0.19.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lecture_26/octave-workspace b/lecture_26/octave-workspace
new file mode 100644
index 0000000..8c437bb
Binary files /dev/null and b/lecture_26/octave-workspace differ