Sharon-rono/Sales-Performance-using-statistics-

A Python-based exploratory data analysis (EDA) and statistical inference project using sales transaction data across regions and store types in Kenya. # Sales-Performance-using-statistics- A Python-based exploratory data analysis (EDA) and statistical inference project using sales transaction data across regions and store types in Kenya. # Sales Statistics Analysis A Python-based exploratory data analysis (EDA) and statistical inference project using sales transaction data across regions and store types in Kenya. --- ## Dataset **File:** `statistics_sales_project_data.csv` **Records:** 1,200 sales transactions (2023) | Column | Type | Description | |---|---|---| | `date` | datetime | Transaction date | | `store_type` | string | Online or Physical | | `region` | string | Sales region (Nairobi, Coast, Western, Rift Valley) | | `marketing_campaign` | string | Whether a campaign was active (Yes/No) | | `units_sold` | integer | Number of units sold per transaction | | `revenue` | float | Revenue generated (KES) | --- ## Project Structure ### 1. Data Loading & Exploration - Loads the CSV using `pandas` - Previews the first 5 rows with `.head()` - Generates descriptive statistics with `.describe()` - Mean revenue: **KES 8,271.97** - Median revenue: **KES 7,723.33** - Revenue mode: **0.0** (indicating zero-revenue transactions exist) - Units sold range: 0–15 ### 2. Data Cleaning - Converts the `date` column from `object` to `datetime64` using `pd.to_datetime()` ### 3. Visualizations | Chart | Description | |---|---| | **Revenue Histogram** | Distribution of revenue across all transactions | | **Revenue Over Time** | Line plot showing daily revenue trend | | **Revenue by Store Type** | Bar chart comparing Online vs Physical store revenue | | **Revenue by Region (Box Plot)** | Revenue spread across Nairobi, Coast, Western, and Rift Valley | | **Sample Mean vs Sample Size** | Demonstrates the Law of Large Numbers | | **Sampling Distribution Histogram** | 200 bootstrap samples (n=30) illustrating the Central Limit Theorem | --- ## Statistical Concepts Covered ### Population vs Sample - **Population:** All possi …