Insert the regression equation for the line of best fit using the scatterplot from your Module Two assignment. Determine r and what it means, including determining the strength of the correlation and discussing how you determine the direction of the association between the two variables.

Real estate

Summary Statistics for MAT 240 Real Estate Data (for dataset in Modules 2, 3, and 4)

n Mean Median Std. Dev. Min Q1 Q3 Max

Listing

price ($)

1,000 342,365 318,000 125,914 135,300 265,250 381,600 987,600

Cost per

square

foot ($)

1,000 169 166 41 71 139 191 344

Square

feet

1,000 2,111 1,881 921 1,101 1,626 2,215 6,516

 

This graph shows the frequency for listing price.

This graph shows the frequency for square feet.

Module Two Notes

Copy and paste any relevant information from your Module Two assignment here to assist you in completing this assignment.

Regression Equation

Insert the regression equation for the line of best fit using the scatterplot from your Module Two assignment.

Determine r

Determine r and what it means, including determining the strength of the correlation and discussing how you determine the direction of the association between the two variables.

Examine the Slope and Intercepts

Draw conclusions from the slope and intercept in the context of this problem and determine the value of only the land.

R-squared Coefficient

Explain what R-squared means in the context of this analysis.

Conclusions

Reflect on the relationship between square feet and sales price by addressing key considerations such as the comparison between your selected region and overall homes in the United States, as well as analyzing how the slope can help identify price changes, how the regression equation can help identify appropriate listing prices, and what square footage ranges the graph would be best used for.