Conclusion

1 files changed, 75 insertions, 59 deletions

diff --git a/CS105MiniProject.ipynb b/CS105MiniProject.ipynb
index a0522d5..4d2fb03 100644
--- a/CS105MiniProject.ipynb
+++ b/CS105MiniProject.ipynb
@@ -21,6 +21,30 @@
   },
   {
    "cell_type": "markdown",
+   "source": [
+    "# Pre-Data Questions & Analysis\n",
+    "\n",
+    "## What data do we have?\n",
+    "\n",
+    "We have data regarding the living situations of students across multiple CS classes. We asked them who they live with, how many people they live with, where they live, whether they work, how much they work, etc. There are a mix of categorical and quantitative datapoints that we will analyze to answer what we want to know:\n",
+    "\n",
+    "## What do we want to know?\n",
+    "\n",
+    "We want to know how various aspects of a student’s home environment go on to affect their employment and school performance. Specifically who they live with and the affects of that.\n",
+    "\n",
+    "## Hypothesis & Predictions\n",
+    "\n",
+    "- Hypothesis 1: There will be a correlation between whether people live with family, friends, or neither and whether or not they work.\n",
+    "- Hypothesis 2: Students who live on-campus are more likely to have roommates of the same major.\n",
+    "- Hypothesis 3: People who live with more people will have a higher GPA on average.\n"
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "bef879a82ebab4fc"
+  },
+  {
+   "cell_type": "markdown",
    "id": "69d8e8ad7c61ba61",
    "metadata": {
     "collapsed": false
@@ -36,8 +60,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.151425Z",
-     "start_time": "2024-02-24T07:21:38.129592Z"
+     "end_time": "2024-02-24T07:34:13.582059Z",
+     "start_time": "2024-02-24T07:34:13.557166Z"
     }
    },
    "outputs": [
@@ -84,8 +108,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.167750Z",
-     "start_time": "2024-02-24T07:21:38.152499Z"
+     "end_time": "2024-02-24T07:34:13.601138Z",
+     "start_time": "2024-02-24T07:34:13.582856Z"
     }
    },
    "outputs": [
@@ -180,8 +204,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.175951Z",
-     "start_time": "2024-02-24T07:21:38.168372Z"
+     "end_time": "2024-02-24T07:34:13.611830Z",
+     "start_time": "2024-02-24T07:34:13.602429Z"
     }
    },
    "outputs": [
@@ -210,8 +234,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.182948Z",
-     "start_time": "2024-02-24T07:21:38.176646Z"
+     "end_time": "2024-02-24T07:34:13.620798Z",
+     "start_time": "2024-02-24T07:34:13.612681Z"
     }
    },
    "outputs": [
@@ -246,8 +270,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.320548Z",
-     "start_time": "2024-02-24T07:21:38.183489Z"
+     "end_time": "2024-02-24T07:34:13.744364Z",
+     "start_time": "2024-02-24T07:34:13.621610Z"
     }
    },
    "outputs": [
@@ -317,8 +341,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.504579Z",
-     "start_time": "2024-02-24T07:21:38.322532Z"
+     "end_time": "2024-02-24T07:34:13.935970Z",
+     "start_time": "2024-02-24T07:34:13.748569Z"
     }
    },
    "id": "c533e52f7d64a4df",
@@ -360,8 +384,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.622759Z",
-     "start_time": "2024-02-24T07:21:38.508034Z"
+     "end_time": "2024-02-24T07:34:14.077650Z",
+     "start_time": "2024-02-24T07:34:13.936947Z"
     }
    },
    "id": "450665f2272bb3a2",
@@ -405,8 +429,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:38.716057Z",
-     "start_time": "2024-02-24T07:21:38.623992Z"
+     "end_time": "2024-02-24T07:34:14.262091Z",
+     "start_time": "2024-02-24T07:34:14.080165Z"
     }
    },
    "id": "1a704a4702ea3f9c",
@@ -451,8 +475,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.046666Z",
-     "start_time": "2024-02-24T07:21:38.717321Z"
+     "end_time": "2024-02-24T07:34:14.822547Z",
+     "start_time": "2024-02-24T07:34:14.266056Z"
     }
    },
    "id": "ae23070caa8a3c88",
@@ -476,39 +500,31 @@
    "outputs": [
     {
      "data": {
-      "text/plain": "Do you currently work?                      No       Yes\nWhat is your current class standing?                    \nFreshman                              0.923077  0.076923\nGraduate                              0.000000  1.000000\nJunior                                0.696078  0.303922\nSenior                                0.725490  0.274510\nSophomore                             0.693182  0.306818",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>Do you currently work?</th>\n      <th>No</th>\n      <th>Yes</th>\n    </tr>\n    <tr>\n      <th>What is your current class standing?</th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Freshman</th>\n      <td>0.923077</td>\n      <td>0.076923</td>\n    </tr>\n    <tr>\n      <th>Graduate</th>\n      <td>0.000000</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>Junior</th>\n      <td>0.696078</td>\n      <td>0.303922</td>\n    </tr>\n    <tr>\n      <th>Senior</th>\n      <td>0.725490</td>\n      <td>0.274510</td>\n    </tr>\n    <tr>\n      <th>Sophomore</th>\n      <td>0.693182</td>\n      <td>0.306818</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "text/plain": "<Figure size 640x480 with 1 Axes>",
-      "image/png": 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"
+      "text/plain": "<Figure size 1000x500 with 2 Axes>",
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
+    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(10, 5))\n",
+    "\n",
     "_ = pd.crosstab(\n",
     "    df['What is your current class standing?'],\n",
     "    df['Do you currently work?'],\n",
-    "    normalize='index'\n",
-    ").plot(kind='bar', stacked=True)\n",
-    "pd.crosstab(\n",
+    ").plot(kind='bar', stacked=True, ax=axes[0])\n",
+    "_ = pd.crosstab(\n",
     "    df['What is your current class standing?'],\n",
     "    df['Do you currently work?'],\n",
     "    normalize='index'\n",
-    ")"
+    ").plot(kind='bar', stacked=True, ax=axes[1])"
    ],
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.136880Z",
-     "start_time": "2024-02-24T07:21:39.048148Z"
+     "end_time": "2024-02-24T07:34:15.002736Z",
+     "start_time": "2024-02-24T07:34:14.823782Z"
     }
    },
    "id": "464b4dec962ea0ae",
@@ -556,8 +572,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.309745Z",
-     "start_time": "2024-02-24T07:21:39.138109Z"
+     "end_time": "2024-02-24T07:34:15.166551Z",
+     "start_time": "2024-02-24T07:34:15.003539Z"
     }
    },
    "id": "101f55892c052d46",
@@ -595,8 +611,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.512158Z",
-     "start_time": "2024-02-24T07:21:39.311676Z"
+     "end_time": "2024-02-24T07:34:15.356893Z",
+     "start_time": "2024-02-24T07:34:15.167983Z"
     }
    },
    "id": "350d4fef50f55e38",
@@ -658,8 +674,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.555055Z",
-     "start_time": "2024-02-24T07:21:39.514908Z"
+     "end_time": "2024-02-24T07:34:15.374530Z",
+     "start_time": "2024-02-24T07:34:15.358439Z"
     }
    },
    "id": "48b809cbd77a656f",
@@ -694,8 +710,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.564411Z",
-     "start_time": "2024-02-24T07:21:39.556730Z"
+     "end_time": "2024-02-24T07:34:15.380613Z",
+     "start_time": "2024-02-24T07:34:15.376125Z"
     }
    },
    "id": "b82779602aa7b791",
@@ -749,8 +765,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.599685Z",
-     "start_time": "2024-02-24T07:21:39.566651Z"
+     "end_time": "2024-02-24T07:34:15.418868Z",
+     "start_time": "2024-02-24T07:34:15.382411Z"
     }
    },
    "id": "24d1f01fdd4ca1d6",
@@ -785,8 +801,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.604065Z",
-     "start_time": "2024-02-24T07:21:39.600815Z"
+     "end_time": "2024-02-24T07:34:15.431282Z",
+     "start_time": "2024-02-24T07:34:15.421577Z"
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    "id": "fd3e73d9f461afd1",
@@ -853,8 +869,8 @@
    "metadata": {
     "collapsed": false,
     "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.625364Z",
-     "start_time": "2024-02-24T07:21:39.604708Z"
+     "end_time": "2024-02-24T07:34:15.480558Z",
+     "start_time": "2024-02-24T07:34:15.434687Z"
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    "id": "b513f8e8241e86e5",
@@ -874,18 +890,18 @@
    "id": "79b83b5ec3c1f9c5"
   },
   {
-   "cell_type": "code",
-   "outputs": [],
-   "source": [],
+   "cell_type": "markdown",
+   "source": [
+    "# Conclusion\n",
+    "\n",
+    "In wanting to figure out in general how various aspects of a student’s home environment go on to affect their employment and school performance, we performed 3 different tests: Comparing what kind of people participants lived with and whether or not they work, students who work on campus and their roommates majors, and the number of people participants lived with and the participant’s GPA. However, using chi-squared tests and pearson correlation, we discovered that none of our hypotheses had any correlation with it. But from here we can delve deeper into our hypothesis, for example why did working not affect student’s GPA’s in the first quarter? What are other potential factors as to why that was the case? In addition, Freshmen were found to not work at major related jobs, whereas juniors were the most likely to work at a major related job.\n",
+    "\n",
+    "Even though none of our hypotheses were proven to be true, we still learned a lot about the data given to us and we can use it to further more questions and assumptions later down the line.\n"
+   ],
    "metadata": {
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-    "ExecuteTime": {
-     "end_time": "2024-02-24T07:21:39.628186Z",
-     "start_time": "2024-02-24T07:21:39.626237Z"
-    }
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-   "id": "55fb116c79c479a1",
-   "execution_count": 17
+   "id": "eb743c217058807f"
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