diff --git a/.ipynb_checkpoints/Solutions-checkpoint.ipynb b/.ipynb_checkpoints/Solutions-checkpoint.ipynb
new file mode 100644
index 0000000..03287dd
--- /dev/null
+++ b/.ipynb_checkpoints/Solutions-checkpoint.ipynb
@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Lab | Inferential statistics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- It is assumed that the mean systolic blood pressure is `μ = 120 mm Hg`. In the Honolulu Heart Study, a sample of `n = 100` people had an average systolic blood pressure of 130.1 mm Hg with a standard deviation of 21.21 mm Hg. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import datetime\n",
+    "import warnings\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import math\n",
+    "from scipy.stats import ttest_ind\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Is the group significantly different (with respect to systolic blood pressure!) from the regular population?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.1 Set up the hypothesis test."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "see below"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.2 Write down all the steps followed for setting up the test."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "https://www.scribbr.com/statistics/hypothesis-testing/\n",
+    "<br>\n",
+    "Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.\n",
+    "<br>\n",
+    "There are 5 main steps in hypothesis testing:<br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### State your research hypothesis as null (H0) and alternate (Ha) hypothesis."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ho: Systolic blood pressure, on average, not higher than regular population. <br>\n",
+    "Ha: Systolic blood pressure, on average, higher than regular population."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Collect data in a way designed to test the hypothesis."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "mean systolic blood pressure is μ = 120 mm Hg <br> \n",
+    "a sample of n = 100 people had an average systolic blood pressure of 130.1 mm Hg <br> \n",
+    "with a standard deviation of 21.21 mm Hg."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Perform an appropriate statistical test."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.7619"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mean_population = 120\n",
+    "sample_mean = 130.1\n",
+    "stdev = 21.21\n",
+    "n = 100\n",
+    "\n",
+    "t = ((sample_mean - mean_population) / (stdev / math.sqrt(n)))\n",
+    "\n",
+    "round(t,5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Decide whether the null hypothesis is supported or refuted."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Present the findings in your results and discussion section."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1.3 Calculate the test statistic by hand and also code it in Python. It should be 4.76190. We will take a look at how to make decisions based on this calculated value."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "see 1.1.2.3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. If you finished the previous question, please go through the code for principal_component_analysis_example provided in the files_for_lab folder ."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.8.5"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Solutions.ipynb b/Solutions.ipynb
index b3e2431..03287dd 100644
--- a/Solutions.ipynb
+++ b/Solutions.ipynb
@@ -2,7 +2,6 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e00a11f1",
    "metadata": {},
    "source": [
     "# Lab | Inferential statistics"
@@ -10,15 +9,30 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2c813f0a",
    "metadata": {},
    "source": [
     "- It is assumed that the mean systolic blood pressure is `μ = 120 mm Hg`. In the Honolulu Heart Study, a sample of `n = 100` people had an average systolic blood pressure of 130.1 mm Hg with a standard deviation of 21.21 mm Hg. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import datetime\n",
+    "import warnings\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import math\n",
+    "from scipy.stats import ttest_ind\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
   {
    "cell_type": "markdown",
-   "id": "120875d3",
    "metadata": {},
    "source": [
     "## 1. Is the group significantly different (with respect to systolic blood pressure!) from the regular population?"
@@ -26,55 +40,131 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d26c43d4",
    "metadata": {},
    "source": [
     "### 1.1 Set up the hypothesis test."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "39c6f717",
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "see below"
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "17c9988a",
    "metadata": {},
    "source": [
     "### 1.2 Write down all the steps followed for setting up the test."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "https://www.scribbr.com/statistics/hypothesis-testing/\n",
+    "<br>\n",
+    "Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.\n",
+    "<br>\n",
+    "There are 5 main steps in hypothesis testing:<br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### State your research hypothesis as null (H0) and alternate (Ha) hypothesis."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ho: Systolic blood pressure, on average, not higher than regular population. <br>\n",
+    "Ha: Systolic blood pressure, on average, higher than regular population."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Collect data in a way designed to test the hypothesis."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "mean systolic blood pressure is μ = 120 mm Hg <br> \n",
+    "a sample of n = 100 people had an average systolic blood pressure of 130.1 mm Hg <br> \n",
+    "with a standard deviation of 21.21 mm Hg."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Perform an appropriate statistical test."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "b09ce149",
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.7619"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mean_population = 120\n",
+    "sample_mean = 130.1\n",
+    "stdev = 21.21\n",
+    "n = 100\n",
+    "\n",
+    "t = ((sample_mean - mean_population) / (stdev / math.sqrt(n)))\n",
+    "\n",
+    "round(t,5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Decide whether the null hypothesis is supported or refuted."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Present the findings in your results and discussion section."
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "63df3700",
    "metadata": {},
    "source": [
     "### 1.3 Calculate the test statistic by hand and also code it in Python. It should be 4.76190. We will take a look at how to make decisions based on this calculated value."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "97f73e20",
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "see 1.1.2.3"
+   ]
   },
   {
    "cell_type": "markdown",
-   "id": "4a7564e5",
    "metadata": {},
    "source": [
     "## 2. If you finished the previous question, please go through the code for principal_component_analysis_example provided in the files_for_lab folder ."
@@ -98,6 +188,19 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.8.5"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,