argument.ipynb proposal.md brfss_2020_cleaned.csv

.ipynb_checkpoints/argument-checkpoint.ipynb

@@ -21,7 +21,8 @@
    "id": "greater-circular",
    "metadata": {},
    "source": [
-    "## Overarching Question: [✏️ PUT YOUR QUESTION HERE ✏️]"
+    "## Overarching Question: \n",
+    "I want to know about what relationship exists, if any, between an adult (18 +) person's age and their weight (I'll use metric).\n"
    ]
   },
   {
@@ -42,7 +43,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "technical-evans",
    "metadata": {},
    "outputs": [],
@@ -54,17 +55,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "overhead-sigma",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (998608375.py, line 6)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  Cell \u001b[0;32mIn[8], line 6\u001b[0;36m\u001b[0m\n\u001b[0;31m    df = pd.(dataset_path)\u001b[0m\n\u001b[0m            ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
    "source": [
     "### 💻 FILL IN YOUR DATASET FILE NAME BELOW 💻 ###\n",
     "\n",
-    "file_name = \"YOUR_DATASET_FILE_NAME.csv\"\n",
+    "file_name = \"brfss_2020_cleaned.csv\"\n",
-    "dataset_path = \"data/\" + file_name\n",
+    "dataset_path = \"data/brfss_2020_cleaned.csv\"\n",
     "\n",
-    "df = pd.read_csv(dataset_path)"
+    "df = pd.(dataset_path)"
    ]
   },
   {
@@ -82,9 +92,11 @@
    "id": "continental-franklin",
    "metadata": {},
    "source": [
-    "**Data Overview**\n",
+    "I'm trying to find out at what age, on average, do people experience a dramatic\n",
-    "\n",
+    "weight gain or loss, if at all?\n",
-    "*✏️ Write 2-3 sentences describing this dataset. Be sure to include where the data comes from and what it contains.*"
+    "I'm curious to find out if such a dramatic increase or decrease in weight can\n",
+    "be captured in a one-time snapshot database, where individuals are NOT tracked \n",
+    "over a period of time, but ONLY once."
    ]
   },
   {
@@ -310,7 +322,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.12.3"
   },
   "toc": {
    "base_numbering": 1,

proposal.md

@@ -1,51 +1,69 @@
-# Project proposal
+# Project proposal
-
+
-This planning document will also form the introduction of your 
+Argument Project
-argument.
+
-
+Nelson Mason - Date: 10/29/2025
-Nelson Mason - Date: 10/29/2025
+
-
+## Overarching Question
-## Overarching Question
+
-
+### What central question are you interested in exploring? Why are you interested in exploring this question?
-### What central question are you interested in exploring? Why are you interested in exploring this question?
+
-
+*This should be the big picture question that you ask; use at least 5
-*This should be the big picture question that you ask; use at least 5
+sentences to describe why you are interested in it.*
-sentences to describe why you are interested in it.*
+
-
+I want to know about what relationship exists, if any, between an adult (18 +) 
-I want to know about what relationship exists, if any, between an adult (18 +) 
+person's age and their weight (I'll use metric).
-person's age and their weight (I'll use metric).
+I'm trying to find out at what age, on average, do people experience a dramatic
-I'm trying to find out at what age, on average, do people experience a dramatic
+weight gain or loss, if at all?
-weight gain or loss, if at all?
+I'm curious to find out if such a dramatic increase or decrease in weight can
-I'm curious to find out if such a dramatic increase or decrease in weight can
+be captured in a one-time snapshot database, where individuals are NOT tracked 
-be captured in a one-time snapshot database, where individuals are NOT tracked 
+over a period of time, but ONLY once.
-over a period of time, but ONLY once.
+
-
+### What specific research questions will you investigate?
-### What specific research questions will you investigate?
+
-
+*List 2-4 specific research questions. Each should be answerable 
-*List 2-4 specific research questions. Each should be answerable 
+using your data set.*
-using your data set.*
+
-What number or percentage can be used to accurately indicate a 
+What number or percentage can be used to accurately indicate a 
-dramatic change in weight by age? How do I determine what "dramatic" is?
+dramatic change in weight by age? How do I determine what "dramatic" is?
-
+
-## Data source
+## Data source
-
+https://www.cdc.gov/brfss/annual_data/annual_2020.htm
-### What data set will you use to answer your overarching question? 
+
-
+### What data set will you use to answer your overarching question? 
-*Give the title of your data set and provide a link to your data.*
+
-
+brfss_2020_cleaned.csv
-### Where is this data from?
+
-
+### Where is this data from?
-*Describe the source of the data set--not just where you downloaded it, but
+
-the person or organization who gathered the data. Explain why you trust them.*
+BRFSS 2020
-
+This lab uses a simplified subset of the BRFSS 2020 dataset, brfss_2020.csv. This notebook explains the variables included as well as the process used to produce this file. Read more about BRFSS at https://www.cdc.gov/brfss/annual_data/annual_2020.htm
-### What is this data about?
+l“The link brfss/annual_data/annual_2020.htm directs to the 2020 Behavioral Risk Factor Surveillance System (BRFSS) annual survey data from the Centers for Disease Control and Prevention (CDC). This dataset includes data from 50 states, the District of Columbia, Guam, and Puerto Rico, collected through a combination of landline and cell phone interviews. The 2020 data reflect changes in the weighting methodology and the inclusion of cell phone respondents that began in 2011, making it non-comparable to data from before that year. 
-
+What the 2020 BRFSS data includes:
-*Describe the nature of the data in the dataset, including the number of rows 
+•	Survey data: Includes approximately 401,958 records and 279 variables.
-and some of the columns which will be important to you.*
+•	Data files: Available in ASCII and SAS Transport formats.
-
+•	Geographic scope: Data collected from all 50 states, the District of Columbia, Guam, and Puerto Rico.
-## Methods 
+•	Methodology: A combination of landline and cell phone data, using updated weighting methods.
-
+•	Documentation: Includes a codebook, survey description, and information on data collection and processing. 
-### How will you use your data set to answer your quantitative questions?
+Key differences from prior years:
-
+•	The 2020 data is not directly comparable to BRFSS data from before 2011 due to the inclusion of cell-phone-only respondents and a revised weighting methodology known as "raking". 
-*For each research question, explain what you will do with the data set 
+How to use the data:
-to answer the question, and how you will present your answer (e.g. a chart or a table).*
+•	Users can access the 2020 survey data and accompanying documentation through the CDC's BRFSS website.
+•	Researchers can use this public data for various studies on health-related behaviors and chronic conditions, as shown in the example research that analyzed the association between sleep, exercise, and coronary heart disease in the 2020 BRFSS data.” – Googe Search
+
+### What is this data about?
+
+2 columns: Age and Weight (metric)
+
+166,426 rows
+
+## Methods
+
+I will use quantitative analysis methods.
+
+### How will you use your data set to answer your quantitative questions?
+
+*For each research question, explain what you will do with the data set 
+to answer the question, and how you will present your answer (e.g. a chart or a table).*
+
+I will create several charts.