Hinchcliff_Megan_MAT_240_Module_Two_Assignment

Selling Price and Area Analysis for D.M. Pan National Real Estate Company 1 Report: Selling Price and Area Analysis for D.M. Pan National Real Estate Company Megan Hinchcliff Southern New Hampshire University

Selling Price Analysis for D.M. Pan National Real Estate Company 2 Introduction This report examines the relationship between the selling price of properties and their size in square feet. The analysis includes information from the Real Estate County Data of 2019 compared to the National Statistics of housing markets. The outcome of this report will aid D.M Pan National Real Estate Company in estimating home prices and the cost of housing for their clients to provide the best advice. Representative Data Sample The following table represents a simple random sample of 30 counties in the Pacific region. Sample Group Listing Price Square Feet Sample Group Listing Price Square Feet Sample 1 $385,500 1,728 Sample 16 $420,800 1,856 Sample 2 $351,00 1,192 Sample 17 $354,600 1,390 Sample 3 $392,200 1,386 Sample 18 $402,300 1,841 Sample 4 $413,100 1,595 Sample 19 $467,100 1,841 Sample 5 $388,400 1,839 Sample 20 $389,300 1,431 Sample 6 $273,300 1,220 Sample 21 $345,500 1,104 Sample 7 $405,100 1,955 Sample 22 $371,200 1,334 Sample 8 $296,800 1,329 Sample 23 $654,300 3,597 Sample 9 $332,900 1,145 Sample 24 $403,900 1,566 Sample 10 $269,300 1,263 Sample 25 $401,700 1,780 Sample 11 $468,200 2,083 Sample 26 $364,800 1,546 Sample 12 $420,400 1,963 Sample 27 $370,000 1,246 Sample 13 $859,000 5,019 Sample 28 $442,800 1,709 Sample 14 $339,600 1,726 Sample 29 $381,400 1,663 Sample 15 $404,100 1,7691 Sample 30 $329,100 1,262

Selling Price Analysis for D.M. Pan National Real Estate Company 4 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 - 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 f(x) = 137.55 x + 162603.35 Pacific Region Square Feet Listing Price The Pattern In the scatterplot graph above, the independent variable (X) represents the square feet of the homes. The dependent variable (Y) represents the home listing prices. The independent and dependent variables have a cause-and-effect relationship where the independent variable is the cause, and the dependent is the effect. The x-axis is independent of other variables controlled by the observer, and the y-axis depends on changes from the independent variable. This makes the independent variable, also known as the predictor, helpful in making predictions. The association between the X and Y variables in the scatterplot is depicted above. When the square footage of homes increases, the listing price also increases. This demonstrates a linear relationship between the two variables, represented in the scatterplot showing a trend line. An outlier in a scatterplot is a variable or variables furthest from the linear regression line. An outlier occurs when there is a natural deviation in the population or through errors and represents

Selling Price Analysis for D.M. Pan National Real Estate Company 5 variables outside the linear relationship. As seen in the Pacific Region scatterplot, an outlier occurs twice in the analysis for the home that is 3,597 with a listing price of $654,300 and a home that is 5,019 square feet with a listing price of $859,000. These outliers occurred because the square feet of the houses are significantly higher than the rest of the sample, increasing the listing price. A house that is 1,800 square feet would be listed at $410,193. The predicted Pacific Region home cost of a 1,800 square-foot house is calculated by the linear equation y = 137.55x + 162603. To use this equation, input 1,800 for x, y=137.55(1,800) + 162603, where y equals 410,193. This equation provides a scientific calculation to estimate home prices and housing costs.