diff --git a/FinalExam_lastname_mnr.ipynb b/FinalExam_lastname_mnr.ipynb
index cfa2358..c2a393b 100644
--- a/FinalExam_lastname_mnr.ipynb
+++ b/FinalExam_lastname_mnr.ipynb
@@ -46,7 +46,8 @@
    "metadata": {},
    "source": [
     "Name:\n",
-    "Mat Number:"
+    "Mat Number:\n",
+    "Jupyter Username:"
    ]
   },
   {
@@ -189,7 +190,7 @@
    "source": [
     "### Question 1: Describing and Testing the Code (4 Points)\n",
     "\n",
-    "Break down and explain each line of the provided code snippet. Additionally, describe the role of the '%' symbol in this context. Why is it necessary within this code?"
+    "a) Break down and explain each line of the provided code snippet. Additionally, describe the role of the '%' symbol in this context. Why is it necessary within this code?"
    ]
   },
   {
@@ -218,24 +219,32 @@
     "    return dataset"
    ]
   },
+  {
+   "cell_type": "raw",
+   "id": "654d26a8-ed35-4c99-b0ab-43c9371a7b21",
+   "metadata": {},
+   "source": [
+    "# add your Answer to a)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "afa185ff-bd11-4c2b-ae55-277217c63bf8",
    "metadata": {},
    "source": [
-    "Test the above code on the *data.csv* and print the result."
+    "b) Test the above code on the *data.csv* and print the result."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 3,
    "id": "5d7a7ac6-5a5c-422c-b310-82b2779cd7fe",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# your code"
+    "# your code for b)"
    ]
   },
   {
@@ -252,7 +261,7 @@
    "metadata": {},
    "source": [
     "### Question 2: Write a short Function (4 Points)\n",
-    "Write a short function which calculates the variance of a dataset and returns it. (hint: to perform x² use ** instead of ^, Pandas is not allowed)"
+    "a) Write **your own** short function which calculates the variance of a dataset and returns it. (hint: to perform x² use ** instead of ^; only core-functions of python are allowed)"
    ]
   },
   {
@@ -277,14 +286,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 1,
    "id": "8df48b65-79be-4a7f-8f47-cdecaa11d390",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "IndentationError",
+     "evalue": "expected an indented block after function definition on line 2 (3899112808.py, line 5)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  Cell \u001b[0;32mIn[1], line 5\u001b[0;36m\u001b[0m\n\u001b[0;31m    def calc_variance(dataset):\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m expected an indented block after function definition on line 2\n"
+     ]
+    }
+   ],
    "source": [
-    "# your function"
+    "# your function for a)\n",
+    "def calc_variance(dataset):\n",
+    "    # your Code"
    ]
   },
   {
@@ -292,19 +312,19 @@
    "id": "c7ff344b-f9d2-4ee8-8ad9-ce3be8ecbb33",
    "metadata": {},
    "source": [
-    "Test your code on the data.csv table below and print the results:"
+    "b) Test your code on the **data.csv** table below and print the results:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 4,
    "id": "705b0c3b-72a0-438d-a9b7-dbb5600aa9c3",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# your test code"
+    "# your test code for b)"
    ]
   },
   {
@@ -329,7 +349,7 @@
    "id": "36d73f9a-2716-4e39-81e8-bb906380f250",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for a):"
    ]
   },
   {
@@ -345,7 +365,7 @@
    "id": "61969d27-0b98-410c-bffc-16a1de912972",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for b):"
    ]
   },
   {
@@ -362,7 +382,7 @@
    "metadata": {},
    "source": [
     "### Question 4: Databases (6 Points)\n",
-    "Put the following code into the correct order and run it. Describe each line with comments:"
+    "Put the following code into a **logical** correct order and run it. Describe each line with comments:"
    ]
   },
   {
@@ -528,7 +548,7 @@
    "metadata": {},
    "source": [
     "### Question 5: Data Analyzer (4 Points)\n",
-    "Design a Python class, DataAnalyzer, to facilitate the analysis and visualization of data stored in a database. The class should provide methods to create a SQLite database from a DataFrame and plot the data using Matplotlib."
+    "a) Design a Python class, DataAnalyzer, to facilitate the analysis and visualization of data stored in a database. The class should provide methods to create a SQLite database from a DataFrame and plot the data using Matplotlib. Write down only the code for the **create_database** method."
    ]
   },
   {
@@ -541,7 +561,7 @@
     "- x_values: A list with x-values.\n",
     "- y_values: A list with y-values.\n",
     "\n",
-    "Method: create_database\n",
+    "**Method: create_database**\n",
     "- Connect to the SQLite database specified by database_name.\n",
     "- Create a table and insert the x and y values.\n",
     "- Print the number of entries in the database after creating.\n",
@@ -560,7 +580,7 @@
    },
    "outputs": [],
    "source": [
-    "# your Class:\n",
+    "# your Class from a):\n",
     "class DataAnalyzer:\n",
     "    def __init__(self, database_name, x_values, y_values):\n",
     "        self.database_name = database_name\n",
@@ -569,7 +589,6 @@
     "\n",
     "    def create_database(self):\n",
     "        # Your Code\n",
-    "        pass\n",
     "\n",
     "    def plot_values(self):\n",
     "        \"\"\"\n",
@@ -588,19 +607,19 @@
    "id": "30605de1-8eb0-4403-a36b-d22418341e9e",
    "metadata": {},
    "source": [
-    "Test your code below on *coordinates.csv*. The name of the database should be your *matr. nr.* You should test both functions! (for import use pandas or csv)"
+    "b) Test your code below on **coordinates.csv**. The name of the database should be your **matr. nr.** You should test both functions! (for import you can use pandas or csv)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "id": "6ea4c395-1246-4530-994b-9c764a5c57ed",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# your test code:"
+    "# your test code from b):"
    ]
   },
   {
@@ -626,19 +645,19 @@
    "id": "f110bc78-13dc-4251-af7a-32bff74ce5bc",
    "metadata": {},
    "source": [
-    "a) Describe the following code with comments."
+    "a) Describe the following code with comments and rename the function. (directly in the code)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 6,
    "id": "3f6d6805-5e97-4fbd-b202-4020e9485643",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "def function(X, y, factor=0.2):\n",
+    "def func_q6(X, y, factor=0.2):\n",
     "    idx = np.arange(X.shape[0])\n",
     "    np.random.shuffle(idx)\n",
     "    X = X[idx]\n",
@@ -666,7 +685,7 @@
    "id": "c9dbe438-5c74-4a02-8ea3-efc0e966e483",
    "metadata": {},
    "source": [
-    "b) Why do we need the above code?"
+    "b) Describe the purpose of the above code?"
    ]
   },
   {
@@ -674,7 +693,7 @@
    "id": "161a52a4-79e2-4401-ba8a-6f680d47771e",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for b):"
    ]
   },
   {
@@ -692,7 +711,7 @@
    "id": "e998c866-416e-457d-aee8-d1034ae21f84",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for c):"
    ]
   },
   {
@@ -708,7 +727,7 @@
    "id": "8d3ec404-4508-413c-9d00-9ce1f24c492f",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for d):"
    ]
   },
   {
@@ -754,7 +773,7 @@
    "id": "d67a67c9-b129-412c-b29b-2869892fcf88",
    "metadata": {},
    "source": [
-    "a) Why do we need linear regression?"
+    "a) Describe the purpose of linear regression?"
    ]
   },
   {
@@ -762,7 +781,7 @@
    "id": "29d16a49-69d4-4c59-921a-33201fa04d95",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for a):"
    ]
   },
   {
@@ -770,7 +789,7 @@
    "id": "43ef5af3-9da0-4dc0-84e1-4731f5687040",
    "metadata": {},
    "source": [
-    "b) What is the difference of using scikit-learn for linear regression and your own method?"
+    "b) How does the result differ when using the scikit-learn library for linear regression and the class above?"
    ]
   },
   {
@@ -778,7 +797,7 @@
    "id": "b6bcafd8-8e89-4fa6-888f-f30a93b019ec",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for b):"
    ]
   },
   {
@@ -786,7 +805,7 @@
    "id": "fdb3bd28-59ca-47ec-a750-79652cbc7d74",
    "metadata": {},
    "source": [
-    "c) Write down the function of the mean squared error? When do you use it?"
+    "c) Write down the function of the mean squared error (mathematically)? When do you use it?"
    ]
   },
   {
@@ -794,7 +813,7 @@
    "id": "791be49f-75ea-43a0-825a-0567ecf72aa1",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for c):"
    ]
   },
   {
@@ -802,7 +821,7 @@
    "id": "24b784d2-005e-4537-b0ce-c534f0303ced",
    "metadata": {},
    "source": [
-    "d) Describe step per step how you would perform linear regression on a given dataset. (more detailed answer)"
+    "d) Describe step by step how you would perform linear regression on a given dataset. (more detailed answer)"
    ]
   },
   {
@@ -810,7 +829,7 @@
    "id": "c6b02c04-2ad1-48f2-9719-14df04846d8e",
    "metadata": {},
    "source": [
-    "Your Answer:"
+    "Your Answer for d):"
    ]
   },
   {
@@ -827,17 +846,17 @@
    "metadata": {},
    "source": [
     "### Question 8: Linear Regression Coding (4 Points)\n",
-    "Perform linear regression on the *winequality-red.csv* with the target *alcohol* (pandas is allowed). Calculate the mean squared error and print it. Perform the task without preprocessing your data. It is necessary to split the data. "
+    "a) Perform linear regression on the **winequality-red.csv** with the target **alcohol** (pandas is allowed). Calculate the **mean squared error** and **print** it. Perform the task without preprocessing your data. It is necessary to **split the data**. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "8f36613b-ecb5-40b0-9918-4119cb8943e2",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#your Code"
+    "# your Code for a)"
    ]
   },
   {
@@ -854,7 +873,7 @@
    "metadata": {},
    "source": [
     "### Question 9: Gaussian Processes (6 Points)\n",
-    "Fit the names to the different kernels below:"
+    "a) Fit the names to the different kernels below:"
    ]
   },
   {
@@ -864,7 +883,7 @@
     "tags": []
    },
    "source": [
-    "Add the Names:\n",
+    "Add the Names to the following lines:\n",
     "\n",
     "1. **... Kernel**: $k(x, x') = \\exp \\left( -2 \\sin^2 \\left( \\frac{\\pi ||x - x'||}{p} \\right) \\right) / \\sigma^2 $\n",
     "2. **... Kernel**: $k(x, x') = x^T x' $\n",
@@ -877,7 +896,7 @@
    "id": "1759762b-5b0a-4e6f-9651-277bc4643fb4",
    "metadata": {},
    "source": [
-    "Fit the above numbers to the code below"
+    "b) Fit the above **numbers** to the lines below."
    ]
   },
   {
@@ -885,7 +904,7 @@
    "id": "0c6ddc30-f804-472c-92d1-8a03d3c3b020",
    "metadata": {},
    "source": [
-    "Your Answer:\n",
+    "Your Answer for b):\n",
     "    function1 = ...\n",
     "    function2 = ...\n",
     "    function3 = ...\n",
@@ -989,6 +1008,30 @@
    "source": [
     "___________________________"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b5042b38-0752-4e23-aae3-3651a5f367cf",
+   "metadata": {},
+   "source": [
+    "### How to submit your file:\n",
+    "1) Save your file in the Jupyter Notebook (Floppy Disk Symbol)\n",
+    "2) Download only your jupyter-file (right-click and download)\n",
+    "3) Change the window to Moodle again (bottom-left corner)\n",
+    "4) Upload your file on Moodle\n",
+    "5) Submit your full exam\n",
+    "    - Finish attempt ...\n",
+    "    - Submit all and finish (First Time)\n",
+    "    - Submit all and finish (Second Time)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5808cbd3-51da-40fd-a770-057156cd7465",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {