"Open up this Markdown cell to see an example where the LaTeX equation must be preceded by a blank line, then everything in that element works OK. \n",
"1. Coefficient of determination $ R^2 $ measures the percentage of the variance in our observations explained by the model. Thus, the higher, the better. As we can see, the value of $R^2$ is quite low. Only $\\approx15\\%$ of the variance is explained by the model, which is very low. Therefore, the linear model is not able to explain the scatter in our observations.\n",
"2. Based on the answer to the previous question, the linear model is not an accurate model. Whether this low level of accuracy is good enough or not, depends on the use we want to give to the model. Would you bet \\$3? What about \\$1,000?\n",
"1. Coefficient of determination $ R^2 $ measures the percentage of the variance in our observations explained by the model. Thus, the higher, the better. As we can see, the value of $R^2$ is quite low. Only $\\approx15\\%$ of the variance is explained by the model, which is very low. Therefore, the linear model is not able to explain the scatter in our observations.\n",
"2. Based on the answer to the previous question, the linear model is not an accurate model. Whether this low level of accuracy is good enough or not, depends on the use we want to give to the model. Would you bet \\$3? What about \\$1,000?\n",
"</p>\n",
"</div>\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "723dd636",
...
...
%% Cell type:markdown id:d14e9d93 tags:
# Standard Elements
See `header_footer.XXXX` files for headers and footers.
%% Cell type:markdown id:fb3ea95b tags:
## Overview
This is where you describe the assignment **briefly**. The last sentence in this cell should not be changed. Feel free to use bullet lists to itemize steps and/or auxiliary files. This assignment includes:
1. a
2. b
3. c
This paragraph is for comments related to programming. As a general rule, always include all package imports in the next cell: **do not** add any sentences that say "here we import packages," **do not** include comments in the import cell and **do not** add more packages later on in the assignment. The only exception to this should be if packages are a key part of the assignment learning goal (i.e., showing how to import, practicing importing, etc). Follow [PEP-8 guidlines for importing](https://peps.python.org/pep-0008/#imports).
Always format the tasks for students in a box with black text and background color #AABAB2. If not clear where the end of the task is and the next content cell starts, use the "end of task" cell.
If you need to specify a function and/or part of the code you must use the HTML code blocks like this <code>name_of_the_function</code>.
Always format the solution in a box with black text and background color #F9E282. Use this message to write the solution itself, or describe the format of the solution (e.g., the solution is written in the code cell below). To clearly indicate where the solution stops and the notebook contents continue, use an additional solution box with message "End of solution."
<divstyle="background-color:#facb8e; color: black; vertical-align: middle; padding:15px; margin: 10px; border-radius: 10px; width: 95%"><p>Minor note (warning). Don't use the CSS danger/warning blocks because they don't display when converting to HTML with pandoc (won't display right on course files on website).</p></div>
1. Coefficient of determination $ R^2 $ measures the percentage of the variance in our observations explained by the model. Thus, the higher, the better. As we can see, the value of $R^2$ is quite low. Only $\approx15\%$ of the variance is explained by the model, which is very low. Therefore, the linear model is not able to explain the scatter in our observations.
2. Based on the answer to the previous question, the linear model is not an accurate model. Whether this low level of accuracy is good enough or not, depends on the use we want to give to the model. Would you bet \$3? What about \$1,000?
1. Coefficient of determination $ R^2 $ measures the percentage of the variance in our observations explained by the model. Thus, the higher, the better. As we can see, the value of $R^2$ is quite low. Only $\approx15\%$ of the variance is explained by the model, which is very low. Therefore, the linear model is not able to explain the scatter in our observations.
2. Based on the answer to the previous question, the linear model is not an accurate model. Whether this low level of accuracy is good enough or not, depends on the use we want to give to the model. Would you bet \$3? What about \$1,000?
</p>
</div>
```
%% Cell type:markdown id:723dd636 tags:
## Task X
Main task
### Task X.1
Sub-task
%% Cell type:code id:63bf2e6a tags:
``` python
code=[]
```
%% Cell type:markdown id:13175788 tags:
%% Cell type:markdown id:2e4617c0 tags:
**See `header_footer.XXXX` files for headers and footers.**
