Project for Applied (MAT-240)

Median Housing Price Prediction Model for D. M. Pan National Real Estate Company
Median Housing Price Model for D. M. Pan National Real Estate Company
[Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.]
Report: Median Housing Price Prediction Model for D. M. Pan National Real Estate Company
[Your Name]
Southern New Hampshire University
Introduction
[Describe the report: Include in this section a brief overview, including the purpose of the report and your approach.]
Data Collection
[Sampling the data: Outline how you obtained your sample data, including the response and predictor variables.]
[Scatterplot: Insert a correctly labeled scatterplot of your chosen variables.]

Data Analysis
[Describe your study briefly. Discuss the requirements of the data sets for a linear regression. Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.]
[Histogram: Insert the histogram of the two variables. Be sure to include appropriate labels.]
[Summary statistics: Insert a table to show the summary statistics.]
[Interpret the graphs and statistics: Describe the shape, center, spread, and any unusual characteristic (outliers, gaps, etc.) and what they mean based on your sample data and the graphs you created.]
[Explain how these characteristics of the sample data compare to the same characteristics of the national population. Also, determine whether your sample is representative of the national housing market sales.]
The Regression Model
[Scatterplot: Include the scatterplot graph of the sample with a line of best fit.]
[Based on your graph, explain whether a regression model can be developed for the data and how.]
[Discuss associations: Explain the associations in the scatterplot, including the direction, strength, form in the context of your model.]
[Find r: Calculate the correlation coefficient and explain how it aligns with your interpretation of the data from the scatterplot.]
The Line of Best Fit
[Regression equation: Insert the regression equation.]
[Interpret regression equation: Interpret the slope and intercept in context.]
[Strength of the equation: Interpret the strength of the regression equation, R-squared.]
[Use regression equation to make predictions: Use the regression equation to make a sample prediction.]
Conclusions
[Summarize findings: Summarize your findings in clear and concise plain language. Outline any questions arising from the study that might be interesting for follow-up research.]