This project displays my skills in Statiscal Analysis, Regression Model in Excel and Data Storytelling
This is my capstone project for the Coursera Business Statistics and Analysis. This Excel project is statistical and prediction analysis of hosing units from US Department of Housing and Urban Development. The project is to analyze and derive insights to the crucial and make business decisions.
- Test Difference in market value between Occupied and Vacant for housing units
- Build a model for predicting market values for housing units.
The following Excel features were used -Formulas -Functions -Visualizations -Prediction analysis
The dataset is of different years each year has its own data.The dataset consists of various housing units and their data, the variables in the data are Region : region which the house is located Bedrooms : number of bedrooms in the housing units. Status: Occupied or Vacant Value: current market value of a unit This is the link of the full metadata here
These are data descriptors for the project for Occupied and Vacant,it was recommended that we identify them.
This is the distribtution of Market value across diiferent years between Occupied and Vacant housing units.
This chart shows the growth in market value for both housing units
Performed a paired t-test to determine the statistical significance of the variables.
I built a regression model to predict Market Value. This is the Link to my submission file here
- Difference in the Market Values is significant only for years 2005 and 2011. In these years the market value of Occupied units was greater than Vacant units.For the remaining years there is no significant difference in the market value across Occupied and Vacant units.
- The regression model now has a R-square of 0.60 since we added the Market Value for year 2011 as an additional 'X' variable.