Explain the associations in the scatterplot, including the direction, strength, form in the context of your model.

Median Housing Price Model for D. M. Pan National Real Estate Company 2

[ Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.]

Report: Housing Price Prediction Model for D. M. Pan National Real Estate Company

[Your Name]

Median Housing Price Prediction Model for D. M. Pan National Real Estate Company 1

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

[ 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 and the regression equation.]

[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.]