Salary Prediction Analysis: Experience vs. Compensation
This project analyzes the relationship between years of experience and salary using linear regression. The dataset contains 30 observations with two variables: YearsExperience and Salary.
Project Highlights:
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Exploratory Data Analysis: Distribution analysis, correlation calculations, outlier detection
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Visualization: Scatter plots, histograms, box plots, regression lines
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Modeling: Linear regression with statistical validation
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Insights: Salary growth patterns, prediction intervals, key metrics
Findings:
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Strong positive correlation (r > 0.98) between experience and salary
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Linear model explains ~95% of salary variance
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Predictable salary progression with increasing experience
Technologies: Python, Pandas, Matplotlib, Seaborn, Statsmodels