diff --git a/Solutions.ipynb b/Solutions.ipynb
index b3e2431..be62ae4 100644
--- a/Solutions.ipynb
+++ b/Solutions.ipynb
@@ -33,12 +33,14 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "39c6f717",
+   "cell_type": "markdown",
+   "id": "0ac74075",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "H0: μ = 120\n",
+    "\n",
+    "H1: μ != 120"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -49,12 +51,16 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b09ce149",
+   "cell_type": "markdown",
+   "id": "1b493c62",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "Level of significance = 0.05\n",
+    "\n",
+    "Calculate the test statistic based on the given information:\n",
+    "- If the test statistic falls in the critical region, then we reject the Null Hypothesis\n",
+    "- If the test statistic falls in the region between the critical region, we accept the Null Hypothesis ie our assumption about the population to be true."
+   ]
   },
   {
    "cell_type": "markdown",
@@ -66,18 +72,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "97f73e20",
    "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4a7564e5",
-   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Statistic is:  4.761904761904759\n"
+     ]
+    }
+   ],
    "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 ."
+    "from statistics import math\n",
+    "\n",
+    "sample_mean = 130.1\n",
+    "pop_mean = 120\n",
+    "pop_std = 21.21\n",
+    "n = 100\n",
+    "statistic = (sample_mean - pop_mean)/(pop_std/math.sqrt(n))\n",
+    "print(\"Statistic is: \", statistic)"
    ]
   }
  ],
@@ -97,7 +112,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.8.8"
   }
  },
  "nbformat": 4,