# [Research Title]: Detailed Technical Analysis

**Status**: [Draft/Final]  
**Author**: [Name]  
**Date**: [YYYY-MM-DD]  
**Datasets Used**: [File names or SQL Table IDs]

---

## 1. Executive Summary
[A 3-5 sentence high-level overview of the problem, the approach, and the primary conclusion.]

## 2. Problem Statement & Objectives
- **Context**: [Why was this research initiated?]
- **Objective**: [What specific questions were we trying to answer?]
- **Hypotheses**: [What did we expect to find?]

## 3. Methodology & Definitions (Exact)
### 3.1 Data Preparation
- **Filters Applied**: [e.g., `user_age > 18`, `status = 'active'`]
- **Time Range**: [Exact start and end dates]
- **Definitions**:
  - `Metric A`: [Exact SQL/Python formula used]
  - `Segment B`: [Exact logic for categorization]

## 4. Technical Challenges & Solutions
| Problem Encountered | Technical Solution | Impact on Results |
| :--- | :--- | :--- |
| [e.g., 20% nulls in Col X] | [Imputed via median per segment] | [Minimal bias introduced] |
| [Join explosion on Table Y] | [Added unique constraint filter] | [Corrected row counts] |

## 5. Detailed Analysis & Results
[In-depth walkthrough of findings. Include statistical significance tests, p-values, and effect sizes where applicable.]

### 5.1 [Key Theme 1]
[Text + Plotly Chart Reference]

### 5.2 [Key Theme 2]
[Text + Plotly Chart Reference]

## 6. Recommendations & Next Steps
1. **[Action 1]**: Based on [Finding X].
2. **[Action 2]**: Next research spike to investigate [Anomaly Y].

---

## 7. Appendix

Links to gitlab repo with analysis code.
