From 06ce1825b3e940630b0f62f15cbc3dd88f6c9ed3 Mon Sep 17 00:00:00 2001
From: Axel Barck-Holst <102673853+AxelHolst@users.noreply.github.com>
Date: Fri, 5 Jul 2024 15:15:16 +0200
Subject: [PATCH] Add Python Syntax Medical Insurance Project and Solution
 notebooks

---
 ...hon Syntax Medical Insurance Project.ipynb | 496 ++++++++++++++++++
 ...x Medical Insurance Project_Solution.ipynb | 451 ++++++++++++++++
 2 files changed, 947 insertions(+)
 create mode 100644 Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project.ipynb
 create mode 100644 Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project_Solution.ipynb

diff --git a/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project.ipynb b/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project.ipynb
new file mode 100644
index 0000000..9b3bae3
--- /dev/null
+++ b/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project.ipynb	
@@ -0,0 +1,496 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7ac921d1",
+   "metadata": {},
+   "source": [
+    "# Python Syntax: Medical Insurance Project"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84c02393",
+   "metadata": {},
+   "source": [
+    "Suppose you are a medical professional curious about how certain factors contribute to medical insurance costs. Using a formula that estimates a person's yearly insurance costs, you will investigate how different factors such as age, sex, BMI, etc. affect the prediction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "05392afb",
+   "metadata": {},
+   "source": [
+    "## Setting up Factors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e433bd9f",
+   "metadata": {},
+   "source": [
+    "1. Our first step is to create the variables for each factor we will consider when estimating medical insurance costs.\n",
+    "\n",
+    "   These are the variables we will need to create:\n",
+    "   - `age`: age of the individual in years\n",
+    "   - `sex`: 0 for female, 1 for male*\n",
+    "   - `bmi`: individual's body mass index\n",
+    "   - `num_of_children`: number of children the individual has\n",
+    "   - `smoker`: 0 for a non-smoker, 1 for a smoker\n",
+    "   \n",
+    "   In the code block below, create the following variables for a **28**-year-old, **nonsmoking woman** who has **three children** and a **BMI** of **26.2**.\n",
+    "   \n",
+    "   **Note**: We are using this [medical insurance dataset](https://www.kaggle.com/mirichoi0218/insurance) as a guide, which unfortunately does not include data for non-binary individuals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7f311028",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create the initial variables below\n",
+    "# Initializing variables\n",
+    "age = 28\n",
+    "smoker = 0  # 1 if smoker, 0 if not a smoker\n",
+    "sex = 0  # 0 if female, 1 if male\n",
+    "num_of_children = 3\n",
+    "bmi = 26.2\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2b7c2cbc",
+   "metadata": {},
+   "source": [
+    "## Working with the Formula"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6db974a5",
+   "metadata": {},
+   "source": [
+    "2. After the declaration of the variables, create a variable called `insurance_cost` that utilizes the following formula:\n",
+    "\n",
+    "   $$\n",
+    "   \\begin{aligned}\n",
+    "   insurance\\_cost = 250*age - 128*sex \\\\\n",
+    "   + 370*bmi + 425*num\\_of\\_children \\\\\n",
+    "   + 24000*smoker - 12500 \\\\\n",
+    "   \\end{aligned}\n",
+    "   $$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "91f86188",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add insurance estimate formula below\n",
+    "# Insurance formula\n",
+    "insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "90e6bbe0",
+   "metadata": {},
+   "source": [
+    "3. Let's display this value in an informative way. Print out the following string in the kernel:\n",
+    "\n",
+    "   ```\n",
+    "   This person's insurance cost is {insurance_cost} dollars.\n",
+    "   ```\n",
+    "   \n",
+    "   You will need to use string concatenation, including the `str()` function to print out the `insurance_cost`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cf6d3790",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This person's insurance cost is 5469.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print out the insurance cost\n",
+    "print(\"This person's insurance cost is \" + str(insurance_cost) + \" dollars.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "203e7e61",
+   "metadata": {},
+   "source": [
+    "## Looking at Age Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c2f65d1",
+   "metadata": {},
+   "source": [
+    "4. We have seen how our formula can estimate costs for one individual. Now let's play with some individual factors to see what role each one plays in our estimation!\n",
+    "\n",
+    "   Let's start with the `age` factor. Using a plus-equal operator, add 4 years to our `age` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "eb23f0c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add 4 years to age\n",
+    "age += 4\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a18a8926",
+   "metadata": {},
+   "source": [
+    "5. Now that we have changed our `age` value, we want to recalculate our insurance cost. Declare a new variable called `new_insurance_cost` in the code block below.\n",
+    "\n",
+    "   Make sure you leave the `insurance_cost` variable the same as in Task 2. We will use it later in our program!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "50f6a44c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d6c2393a",
+   "metadata": {},
+   "source": [
+    "6. Next, we want to find the difference between our `new_insurance_cost` and `insurance_cost`. To do this, let's create a new variable called `change_in_insurance_cost` and set it equal to the difference between `new_insurance_cost` and `insurance_cost`.\n",
+    "\n",
+    "   Note: depending on the order that we subtract (eg., `new_insurance_cost - insurance_cost` vs. `insurance_cost - new_insurance_cost`), we'll get a positive or negative version of the same number. To make this difference interpretable, let's calculate `new_insurance cost - insurance_cost`. Then we can say, \"people who are four years older have estimated insurance costs that are `change_in_insurance_cost` dollars different, where the sign of `change_in_insurance_cost` tells us whether the cost is higher or lower\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "6b72279c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2e6df15c",
+   "metadata": {},
+   "source": [
+    "7. We want to display this information in an informative way similar to the output from instruction 3. In the code block below, print the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "\n",
+    "   ```\n",
+    "   The change in cost of insurance after increasing the age by 4 years is XXX dollars.\n",
+    "   ```\n",
+    "   \n",
+    "   Doing this will tell us how 4 years in age affects medical insurance cost estimates assuming that all other variables remain the same.\n",
+    "   \n",
+    "   You will need to concatenate strings and use the `str()` method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "0a999d40",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in cost of insurance after increasing the age by 4 years is 1000.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"The change in cost of insurance after increasing the age by 4 years is \" + str(change_in_insurance_cost) + \" dollars.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23bc90cf",
+   "metadata": {},
+   "source": [
+    "## Looking at BMI Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81747d10",
+   "metadata": {},
+   "source": [
+    "8. Now that you have looked at the age factor, let's move onto another one: BMI. First, we have to redefine our `age` variable to be its original value.\n",
+    "\n",
+    "   Set `age` to `28`. This will reset its value and allow us to focus on just the change in the BMI factor moving forward.\n",
+    "   \n",
+    "   On the next line, using the plus-equal operator, add `3.1` to our `bmi` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "53ea7df3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Reset age to 28\n",
+    "age = 28\n",
+    "\n",
+    "# Add 3.1 to BMI\n",
+    "bmi += 3.1\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "febe2c07",
+   "metadata": {},
+   "source": [
+    "9. Now let's find out how a change in BMI affects insurance costs. Our next steps are pretty much the same as we have done before when looking at `age`.\n",
+    "   1. Below the line where `bmi` was increased by `3.1`, rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "   2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "   3. Display the following string in the output terminal, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "   \n",
+    "   ```py\n",
+    "   The change in estimated insurance cost after increasing BMI by 3.1 is XXX dollars.\n",
+    "   ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "19d121c8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated insurance cost after increasing BMI by 3.1 is 1147.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "\n",
+    "# Calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "\n",
+    "print(\"The change in estimated insurance cost after increasing BMI by 3.1 is \" + str(change_in_insurance_cost) + \" dollars.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26c3c473",
+   "metadata": {},
+   "source": [
+    "## Looking at Male vs. Female Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e0c96041",
+   "metadata": {},
+   "source": [
+    "10. Let's look at the effect sex has on medical insurance costs. Before we make any additional changes, first reassign your `bmi` variable back to its original value of `26.2`.\n",
+    "\n",
+    "    On a new line of code in the code block below, reassign the value of `sex` to `1`. A reminder that `1` identifies male individuals and `0` identifies female individuals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ae87bfec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Reset BMI to original value\n",
+    "bmi = 26.2\n",
+    "\n",
+    "# Change sex to male\n",
+    "sex = 1\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da20c656",
+   "metadata": {},
+   "source": [
+    "11. Perform the steps below!\n",
+    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "    2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "    3. Display the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "    ```\n",
+    "    The change in estimated cost for being male instead of female is XXX dollars.\n",
+    "    ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ce2da0e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated insurance cost for being male instead of female is -128.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "\n",
+    "# Calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "\n",
+    "print(\"The change in estimated insurance cost for being male instead of female is \" + str(change_in_insurance_cost) + \" dollars.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f652d964",
+   "metadata": {},
+   "source": [
+    "12. Notice that this time you got a negative value for `change_in_insurance_cost`. Let's think about what that means. We changed the sex variable from `0` (female) to `1` (male) and it decreased the estimated insurance costs.\n",
+    "\n",
+    "    This means that men tend to have lower medical costs on average than women. Reflect on the other findings you have dug up from this investigation so far."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1190661d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "deae95f4",
+   "metadata": {},
+   "source": [
+    "## Extra Practice"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2e44bb53",
+   "metadata": {},
+   "source": [
+    "13. Great job on the project!!!\n",
+    "\n",
+    "    So far we have looked at 3 of the 5 factors in the insurance costs formula. The two remaining are `smoker` and `num_of_children`. If you want to keep challenging yourself, spend some time investigating these factors!\n",
+    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "    2. Save the difference between `new_insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "    3. Display the information below!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "ee321873",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated cost for being a smoker is 23872.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Change smoker status to 1 (smoker)\n",
+    "smoker = 1\n",
+    "\n",
+    "# Calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "\n",
+    "# Calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "\n",
+    "print(\"The change in estimated cost for being a smoker is \" + str(change_in_insurance_cost) + \" dollars.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "de87f356",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated cost for having 5 children is 24722.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Change number of children to 5\n",
+    "num_of_children = 5\n",
+    "\n",
+    "# Calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "\n",
+    "# Calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "\n",
+    "print(\"The change in estimated cost for having 5 children is \" + str(change_in_insurance_cost) + \" dollars.\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project_Solution.ipynb b/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project_Solution.ipynb
new file mode 100644
index 0000000..70b5f0d
--- /dev/null
+++ b/Python Syntax Medical Insurance Project/Python Syntax Medical Insurance Project_Solution.ipynb	
@@ -0,0 +1,451 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "95c4ebc5",
+   "metadata": {},
+   "source": [
+    "# Python Syntax: Medical Insurance Project"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97508254",
+   "metadata": {},
+   "source": [
+    "Suppose you are a medical professional curious about how certain factors contribute to medical insurance costs. Using a formula that estimates a person's yearly insurance costs, you will investigate how different factors such as age, sex, BMI, etc. affect the prediction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c908a017",
+   "metadata": {},
+   "source": [
+    "## Setting up Factors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da275cba",
+   "metadata": {},
+   "source": [
+    "1. Our first step is to create the variables for each factor we will consider when estimating medical insurance costs.\n",
+    "\n",
+    "   These are the variables we will need to create:\n",
+    "   - `age`: age of the individual in years\n",
+    "   - `sex`: 0 for female, 1 for male*\n",
+    "   - `bmi`: individual's body mass index\n",
+    "   - `num_of_children`: number of children the individual has\n",
+    "   - `smoker`: 0 for a non-smoker, 1 for a smoker\n",
+    "   \n",
+    "   In the code block below, create the following variables for a **28**-year-old, **nonsmoking woman** who has **three children** and a **BMI** of **26.2**.\n",
+    "   \n",
+    "   **Note**: We are using this [medical insurance dataset](https://www.kaggle.com/mirichoi0218/insurance) as a guide, which unfortunately does not include data for non-binary individuals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3f11ddb3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# initializing variables\n",
+    "age = 28\n",
+    "smoker = 0 # 1 if smoker 0 if not a smoker\n",
+    "sex = 0 # 0 if female 1 if male\n",
+    "num_of_children = 3\n",
+    "bmi = 26.2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6f182a4c",
+   "metadata": {},
+   "source": [
+    "## Working with the Formula"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b23a6f40",
+   "metadata": {},
+   "source": [
+    "2. After the declaration of the variables, create a variable called `insurance_cost` that utilizes the following formula:\n",
+    "\n",
+    "   $$\n",
+    "   \\begin{aligned}\n",
+    "   insurance\\_cost = 250*age - 128*sex \\\\\n",
+    "   + 370*bmi + 425*num\\_of\\_children \\\\\n",
+    "   + 24000*smoker - 12500 \\\\\n",
+    "   \\end{aligned}\n",
+    "   $$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c8305f0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# insurance formula written out\n",
+    "insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "611ab52c",
+   "metadata": {},
+   "source": [
+    "3. Let's display this value in an informative way. Print out the following string in the kernel:\n",
+    "\n",
+    "   ```\n",
+    "   This person's insurance cost is {insurance_cost} dollars.\n",
+    "   ```\n",
+    "   \n",
+    "   You will need to use string concatenation, including the `str()` function to print out the `insurance_cost`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7b182d95",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This person's insurance cost is 5469.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# print out the insurance cost\n",
+    "print(\"This person's insurance cost is \" + str(insurance_cost) + \" dollars.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dad95da1",
+   "metadata": {},
+   "source": [
+    "## Looking at Age Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91b3c35e",
+   "metadata": {},
+   "source": [
+    "4. We have seen how our formula can estimate costs for one individual. Now let's play with some individual factors to see what role each one plays in our estimation!\n",
+    "\n",
+    "   Let's start with the `age` factor. Using a plus-equal operator, add 4 years to our `age` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "893b53ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# add 4 years to age\n",
+    "age += 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "86297956",
+   "metadata": {},
+   "source": [
+    "5. Now that we have changed our `age` value, we want to recalculate our insurance cost. Declare a new variable called `new_insurance_cost` in the code block below.\n",
+    "\n",
+    "   Make sure you leave the `insurance_cost` variable the same as in Task 2. We will use it later in our program!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f5318944",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91b3a2de",
+   "metadata": {},
+   "source": [
+    "6. Next, we want to find the difference between our `new_insurance_cost` and `insurance_cost`. To do this, let's create a new variable called `change_in_insurance_cost` and set it equal to the difference between `new_insurance_cost` and `insurance_cost`.\n",
+    "\n",
+    "   Note: depending on the order that we subtract (eg., `new_insurance_cost - insurance_cost` vs. `insurance_cost - new_insurance_cost`), we'll get a positive or negative version of the same number. To make this difference interpretable, let's calculate `new_insurance cost - insurance_cost`. Then we can say, \"people who are four years older have estimated insurance costs that are `change_in_insurance_cost` dollars different, where the sign of `change_in_insurance_cost` tells us whether the cost is higher or lower\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "b5c1e242",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a5432c0",
+   "metadata": {},
+   "source": [
+    "7. We want to display this information in an informative way similar to the output from instruction 3. In the code block below, print the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "\n",
+    "   ```\n",
+    "   The change in cost of insurance after increasing the age by 4 years is XXX dollars.\n",
+    "   ```\n",
+    "   \n",
+    "   Doing this will tell us how 4 years in age affects medical insurance cost estimates assuming that all other variables remain the same.\n",
+    "   \n",
+    "   You will need to concatenate strings and use the `str()` method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e48f76ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in cost of insurance after increasing the age by 4 years is 1000.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"The change in cost of insurance after increasing the age by 4 years is \" + str(change_in_insurance_cost) + \" dollars.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d5d05f3",
+   "metadata": {},
+   "source": [
+    "## Looking at BMI Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ca1f623",
+   "metadata": {},
+   "source": [
+    "8. Now that you have looked at the age factor, let's move onto another one: BMI. First, we have to redefine our `age` variable to be its original value.\n",
+    "\n",
+    "   Set `age` to `28`. This will reset its value and allow us to focus on just the change in the BMI factor moving forward.\n",
+    "   \n",
+    "   On the next line, using the plus-equal operator, add `3.1` to our `bmi` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "8063ff67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# rewrite age as original age\n",
+    "age = 28\n",
+    "\n",
+    "# add 3.1 to bmi\n",
+    "bmi += 3.1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da2ef25a",
+   "metadata": {},
+   "source": [
+    "9. Now let's find out how a change in BMI affects insurance costs. Our next steps are pretty much the same as we have done before when looking at `age`.\n",
+    "   1. Below the line where `bmi` was increased by `3.1`, rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "   2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "   3. Display the following string in the output terminal, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "   \n",
+    "   ```py\n",
+    "   The change in estimated insurance cost after increasing BMI by 3.1 is XXX dollars.\n",
+    "   ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "1ece3cdf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated insurance cost after increasing BMI by 3.1 is 1147.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "# calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "print(\"The change in estimated insurance cost after increasing BMI by 3.1 is \" + str(change_in_insurance_cost) + \" dollars.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "11e37d92",
+   "metadata": {},
+   "source": [
+    "## Looking at Male vs. Female Factor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a5d9108",
+   "metadata": {},
+   "source": [
+    "10. Let's look at the effect sex has on medical insurance costs. Before we make any additional changes, first reassign your `bmi` variable back to its original value of `26.2`.\n",
+    "\n",
+    "    On a new line of code in the code block below, reassign the value of `sex` to `1`. A reminder that `1` identifies male individuals and `0` identifies female individuals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "1fcf7d9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# rewrite bmi as original value\n",
+    "bmi = 26.2\n",
+    "\n",
+    "# male vs. female factor\n",
+    "# change value of sex to 1\n",
+    "sex = 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e1e43161",
+   "metadata": {},
+   "source": [
+    "11. Perform the steps below!\n",
+    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "    2. Save the difference between `new_insurance_cost` and `insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "    3. Display the following string, where `XXX` is replaced by the value of `change_in_insurance_cost`:\n",
+    "    ```\n",
+    "    The change in estimated cost for being male instead of female is XXX dollars.\n",
+    "    ```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "1f2ae3c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The change in estimated insurance cost for being male instead of female is -128.0 dollars.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# calculate the new insurance cost\n",
+    "new_insurance_cost = 250 * age - 128 * sex + 370 * bmi + 425 * num_of_children + 24000 * smoker - 12500\n",
+    "# calculate change between the new insurance cost and original insurance cost\n",
+    "change_in_insurance_cost = new_insurance_cost - insurance_cost\n",
+    "print(\"The change in estimated insurance cost for being male instead of female is \" + str(change_in_insurance_cost) + \" dollars.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7bd3d8e",
+   "metadata": {},
+   "source": [
+    "12. Notice that this time you got a negative value for `change_in_insurance_cost`. Let's think about what that means. We changed the sex variable from `0` (female) to `1` (male) and it decreased the estimated insurance costs.\n",
+    "\n",
+    "    This means that men tend to have lower medical costs on average than women. Reflect on the other findings you have dug up from this investigation so far."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5a0ab991",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2220ee2e",
+   "metadata": {},
+   "source": [
+    "## Extra Practice"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b457067e",
+   "metadata": {},
+   "source": [
+    "13. Great job on the project!!!\n",
+    "\n",
+    "    So far we have looked at 3 of the 5 factors in the insurance costs formula. The two remaining are `smoker` and `num_of_children`. If you want to keep challenging yourself, spend some time investigating these factors!\n",
+    "    1. Rewrite the insurance cost formula and assign it to the variable name `new_insurance_cost`.\n",
+    "    2. Save the difference between `new_insurance_cost` in a variable called `change_in_insurance_cost`.\n",
+    "    3. Display the information below!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e360256",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9cc366d9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}