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Merge pull request microsoft#524 from Rayycoding/raySolution
Ray solution
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1-Introduction/04-stats-and-probability/assignment.ipynb

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{
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"cell_type": "markdown",
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"source": [
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"## Introduction to Probability and Statistics\r\n",
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"## Assignment\r\n",
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"\r\n",
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"## Introduction to Probability and Statistics\n",
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"## Assignment\n",
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"\n",
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"In this assignment, we will use the dataset of diabetes patients taken [from here](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html)."
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],
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"metadata": {}
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"cell_type": "code",
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"execution_count": 13,
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"source": [
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"import pandas as pd\r\n",
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"import numpy as np\r\n",
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"\r\n",
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"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\r\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\n",
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"df.head()"
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],
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"outputs": [
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{
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"cell_type": "markdown",
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"source": [
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"\r\n",
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"In this dataset, columns as the following:\r\n",
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"* Age and sex are self-explanatory\r\n",
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"* BMI is body mass index\r\n",
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"* BP is average blood pressure\r\n",
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"* S1 through S6 are different blood measurements\r\n",
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"* Y is the qualitative measure of disease progression over one year\r\n",
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"\r\n",
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"Let's study this dataset using methods of probability and statistics.\r\n",
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"\r\n",
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"\n",
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"In this dataset, columns as the following:\n",
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"* Age and sex are self-explanatory\n",
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"* BMI is body mass index\n",
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"* BP is average blood pressure\n",
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"* S1 through S6 are different blood measurements\n",
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"* Y is the qualitative measure of disease progression over one year\n",
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"\n",
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"Let's study this dataset using methods of probability and statistics.\n",
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"\n",
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"### Task 1: Compute mean values and variance for all values"
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],
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"metadata": {}
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{
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"cell_type": "markdown",
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"source": [
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"### Task 4: Test the correlation between different variables and disease progression (Y)\r\n",
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"\r\n",
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"### Task 4: Test the correlation between different variables and disease progression (Y)\n",
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"\n",
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"> **Hint** Correlation matrix would give you the most useful information on which values are dependent."
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],
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"metadata": {}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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}

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