This repository showcases a comprehensive application of statistical methodologies to solve real-world business problems using Microsoft Excel. 📂 Project Case Studies
1. California Real Estate: Descriptive Analysis Methodology: Performed an exploratory data audit of property markets. Key Skills: Mean/Median analysis, standard deviation, and data visualization to identify pricing trends and market outliers.
![California Real Estate descriptive Analysis]
![Central Tendency and Market Volatility]
![Price vs. Area]
2. Confidence Interval Analysis: Inferential Statistics Methodology: Moved beyond raw data to estimate population parameters with 95% confidence. Key Skills: Calculated margins of error and confidence intervals to provide actionable business ranges for decision-making.
![Inferential Statistics 'Confidence Interval']
3. Weight and Payroll: Statistical Inference Audit Methodology: Applied hypothesis testing to workplace and physiological data. Key Skills: Used T-testing and Z-testing to determine if observed variations in payroll and weight metrics were statistically significant or due to chance.
![Statistical Inference 'Weight Loss'l]
1[Hypothesis Testing HR Audit]
4. Used Car Price Prediction: Multiple Linear Regression Methodology: Built a predictive model to estimate vehicle values based on mileage, year, and brand prestige. Log Transformation: Applied LN transforms to fix data skewness and ensure model linearity. Interactive Tool: Integrated an EXP function to convert abstract log-results back into real-world dollar valuations (e.g., predicting a 2020 Renault at $3,374).
![Predictive Model Summary]
![Price Predictor]
🛠️ Technical Toolkit Analysis: Descriptive Statistics, Inferential Audits, Hypothesis Testing (P-Values, T-Stats). Modeling: Ordinary Least Squares (OLS) Regression, Dummy Variables, Log-Normal Transformations. Visualization: Scatter plot matrices, Linearity/Homoscedasticity checks.