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[lab-confidence-intervals] Alexandre Garanhao #205

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113 changes: 104 additions & 9 deletions your-code/main.ipynb
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -9,14 +10,18 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Libraries"
"# Libraries\n",
"import pandas as pd\n",
"import numpy as np\n",
"import scipy.stats as st"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -32,14 +37,29 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"(172.14308590115726, 174.79024743217607)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# your code here"
"# your code here\n",
"heights = [167, 167, 168, 168, 168, 169, 171, 172, 173, 175, 175, 175, 177, 182, 195]\n",
"np.mean(heights)\n",
"st.norm.interval(0.80, loc=np.mean(heights), scale=4/np.sqrt(15))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -51,14 +71,87 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 37,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"105"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# your code here"
"lista = [ 1 for item in range(27)] + [ 0 for item in range(105-27)]"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.43705881545081005"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.std(lista)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.2571428571428571"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.mean(lista)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(0.38239734376337375, 0.49172028713824634)\n",
"(0.36690157607248103, 0.507216054829139)\n"
]
}
],
"source": [
"# your code here\n",
"\n",
"print(st.norm.interval(0.80, loc=27/105, scale=np.std(lista)/np.sqrt(105)))\n",
"print(st.norm.interval(0.90, loc=27/105, scale=np.std(lista)/np.sqrt(105)))"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -84,6 +177,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -102,6 +196,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand Down Expand Up @@ -145,7 +240,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
"version": "3.11.2"
}
},
"nbformat": 4,
Expand Down