{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# UC San Diego: Modeling and Data Analysis\n",
"### Instructor: C. Alex Simpkins Ph.D. / TA: Sagarika Sardesai\n",
"## Final Project Title (change this to your project's title)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Permissions\n",
"\n",
"Place an `X` in the appropriate bracket below to specify if you would like your group's project to be made available to the public. (Note that student names will be included (but PIDs will be scraped from any groups who include their PIDs).\n",
"\n",
"* [ ] YES - make available\n",
"* [ ] NO - keep private"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Names\n",
"\n",
"- Black Panther\n",
"- Black Widow\n",
"- Hulk\n",
"- Iron Man\n",
"- Thor\n",
"- Vision\n",
"- Wanda"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Overview"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Write a clear, 3-4 sentence summary of what you did and why."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Research Question"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* One sentence that describes the question you address in your project. Make sure what you’re measuring (variables) to answer your question is clear!\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"## Background & Prior Work"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Include a general introduction to your topic\n",
"- Include explanation of what work has been done previously\n",
"- Include citations or links to previous work\n",
"\n",
"This section will present the background and context of your topic and question in a few paragraphs. Include a general introduction to your topic and then describe what information you currently know about the topic after doing your initial research. Include references to other projects who have asked similar questions or approached similar problems. Explain what others have learned in their projects.\n",
"\n",
"Find some relevant prior work, and reference those sources, summarizing what each did and what they learned. Even if you think you have a totally novel question, find the most similar prior work that you can and discuss how it relates to your project.\n",
"\n",
"References can be research publications, but they need not be. Blogs, GitHub repositories, company websites, etc., are all viable references if they are relevant to your project. It must be clear which information comes from which references. (2-3 paragraphs, including at least 2 references)\n",
"\n",
" **Use inline citation through Markdown footnotes to specify which references support which statements** \n",
"\n",
"For example: \n",
"\n",
"Traditional approaches to robotic manipulation in industry have relied upon simplifying the problem such that simple manipulators designed for a single purpose could be used (pinchers, pick-and-place machines, etc), however in order to bring robots into uncertain, changing environments with humans and in order to task them with multiple dynamic operations, a totally new approach must be considered[^simpkins2012].\n",
"\n",
"\n",
" You need enough references to fully explain and back up important facts. \n",
"\n",
"[^simpkins2012]: Simpkins, C. (17 Aug 2012) Towards methods for robotic systems capable of human-level dexterity in manipulation and locomotion. *International Conference on Mechatronic System and Measurement Technology*. http://casimpkinsjr.radiantdolphinpress.com/files/simpkins_ICMSMT2012c.pdf\n",
"\n",
"References should be relevant to the project, not randomly chosen vaguely related topics. If possible you should include a web link as demonstrated above.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hypothesis\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Include your team's research hypothesis and null hypothesis\n",
"- Ensure that this hypothesis is clear and concise\n",
"\n",
"Your hypothesis should NOT include your interpretation or assumptions about an outcome, only the highly refined version of your question. Your interpretation should be determined by the analysis and results, and will be discussed in the conclusion of your report.\n",
" (2-3 sentences)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Dataset(s)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Fill in your dataset information here*\n",
"\n",
"(Copy this information for each dataset)\n",
"- Dataset Name:\n",
"- Link to the dataset:\n",
"- Number of observations:\n",
"\n",
"1-2 sentences describing each dataset. \n",
"\n",
"If you plan to use multiple datasets, add 1-2 sentences about how you plan to combine these datasets."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Wrangling"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Explain steps taken to pull the data you need into Python."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"## YOUR CODE HERE"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Cleaning"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Describe your data cleaning steps here."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"## YOUR CODE HERE\n",
"## FEEL FREE TO ADD MULTIPLE CELLS PER SECTION"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Visualization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* This is a good place for some relevant visualizations related to any exploratory data anlayses (EDA) you did after the basic cleaning."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Analysis, Model, Validation & Results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Include cells that describe the steps in your data analysis.\n",
"* your model could go here unless you have already created a separate section\n",
"* You'll likely also have some visualizations here as well.\n",
"* You should include any statistics, descriptive and inferential, regression or classification models here that go beyond your EDA\n",
"* Spend time describing your motivation for the model, analysis, and your assessment of the outcome, without going into the conclusion"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"## YOUR CODE HERE\n",
"## FEEL FREE TO ADD MULTIPLE CELLS PER SECTION"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Conclusion & Discussion"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Discussion of your results and how they address your experimental question(s).\n",
"* Come to a conclusion about your questions and hypothesis (remember we can only reject or fail to reject the null, we cannot accept the hypothesis. \n",
"* What are the implications of your results?\n",
"* Do you have any insights about your statistical approach or modeling here?\n",
"* Would you use a different model if going further?\n",
"* Discuss limitations of your analyses.\n",
"* You can also discuss future directions this work could be taken."
]
},
{
"cell_type": "code",
"execution_count": null,
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}