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Terro's real estate agency to identify the most relevant features affecting house pricing.

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Real_Estate_Data_Analysis

Project: Terro's Real Estate Data Analysis

Situation:

  • Conducted exploratory data analysis (EDA) for Terro's real estate agency to identify the most relevant features affecting house pricing in Boston.

Task:

  • Analyzed a dataset of 506 houses to understand the factors influencing property values, including crime rates, pollution levels, education facilities, and more.

Action:

  • Utilized Excel's Data Analysis Tool Pack to perform:
    • Summary statistics analysis to comprehend the data's characteristics.
    • Histogram plotting to visualize the distribution of average house prices (Avg_Price).
    • Computation of a covariance matrix to assess variable relationships.
    • Creation of a correlation matrix to identify strong positive and negative correlations.

Result:

  • Identified key insights, including significant correlations between variables.
  • Built regression models to predict house prices based on independent variables.
  • Determined the significance of factors impacting house prices.
  • Contributed to data-driven decision-making for pricing strategies.

This project demonstrates my proficiency in data analysis, statistical tools, and regression modeling, highlighting my ability to derive actionable insights from complex datasets.

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Terro's real estate agency to identify the most relevant features affecting house pricing.

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