Completed proposal for project argument.

Looking forward to this project because it's allows me to use concepts I learned in undergrad

proposal.md

@@ -7,33 +7,48 @@ argument.
 
 ### 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
-sentences to describe why you are interested in it.*
+How do students’ daily lifestyle habits—such as study time, sleep, physical activity, and social engagement—affect their academic performance and stress levels?
+This question is important because academic success is often viewed through the narrow lens of study hours alone, while other lifestyle factors may play equally significant roles. As students navigate demanding academic environments, understanding how their choices outside the classroom impact their GPA and well-being can lead to more effective support systems and healthier routines. I’m interested in this question because I want to be able to bridge academic performance with holistic wellness, offer insights that could inform school policies, counseling programs, and personal time management strategies. This topic resonates with broader conversations about student mental health and the importance of balance in education. By analyzing these relationships we can move beyond anecdotal advice and provide evidence-based recommendations.
 
 ### What specific research questions will you investigate?
-
-*List 2-4 specific research questions. Each should be answerable 
-using your data set.*
+- Which lifestyle factors (study hours, sleep, physical activity, social time) are most strongly correlated with GPA?
+- Is there a threshold of study hours beyond which GPA plateaus or declines?
+- How do students with high stress levels differ in lifestyle habits compared to those with low stress?
+- Are there clusters of students with similar lifestyle profiles and academic outcomes?
 
 ## Data source
 
 ### 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.*
+Student Lifestyle Dataset
+Link: https://www.kaggle.com/datasets/steve1215rogg/student-lifestyle-dataset
 
 ### 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.*
+This dataset was published on Kaggle by Sumit Kumar. It was created for educational and analytical purposes.The data was self-reported by students who participated in the survey through Google Forms. The form was shared with students across different educational institutions, primarily focusing on those in India and other South Asian countries, where the CGPA system is widely used. This ensures that the dataset is contextually relevant to the educational environment in these regions.
 
 ### What is this data about?
 
-*Describe the nature of the data in the dataset, including the number of rows 
-and some of the columns which will be important to you.*
+This dataset, titled "Daily Lifestyle and Academic Performance of Students", contains data from 2,000 students collected via a Google Form survey. It includes information on study hours, extracurricular activities, sleep, socializing, physical activity, stress levels, and CGPA. The data covers an academic year from August 2023 to May 2024 and reflects student lifestyles. This dataset can help analyze the impact of daily habits on academic performance and student well-being.
+
+File Name: Daily_Lifestyle_and_Academic_Performance.csv
+File Format: CSV
+Number of Records: 2000 rows
+Number of Columns: 8 columns
+Column Names: Student ID, Study Hours, Extracurricular Hours, Sleep Hours, Social Hours, Physical Activity Hours, Stress Level, CGPA
 
 ## 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).*
+- Correlation Analysis (RQ1):
+    - Calculate correlation coefficients between GPA and each lifestyle variable.
+    - Visualize using a heatmap and summarized in a correlation table.
+- Threshold Analysis (RQ2):
+    - Create scatter plots and fit regression curves to explore how GPA changes with increasing study hours.
+    - Identify any inflection points where additional study time no longer improves GPA.
+- Group Comparison (RQ3):
+    - Group by stress level (Low, Moderate, High) and compare average lifestyle habits using bar charts and box plots.
+    - test for statistically significant differences.
+- Clustering (RQ4):
+    - Use K-means clustering to group students based on their lifestyle habits.
+    - Visualize using radar charts and compare by average GPA and stress level.