Module 3 Assignment for Applied Statistics

Housing Price Prediction Model for D.M. Pan Real Estate Company Caitlynne Moreland Southern New Hampshire University

Median Housing Price Prediction Model for D.M. Pan National Real Estate Company 2 Module Two Notes Square Feet Listing Price 1,663 250,300 1,773 279,300 1,777 174,900 1,792 291,100 1,908 229,600 1,964 217,500 1,996 207,500 2,007 208,000 2,104 213,600 2,133 190,100 2,199 252,500 2,200 298,500 2,278 308,500 2,279 265,900 2,295 254,800 2,328 293,000 2,357 336,800 2,385 269,000 2,438 288,300 2,450 256,800 2,476 316,900 2,479 273,600 2,482 295,100 2,532 268,600 2,538 279,400 2,585 326,400 4,177 476,600 4,562 532,300 4,947 630,100 5,719 564,900 0 1000 2000 3000 4000 5000 6000 7000 $0 $100,000 $200,000 $300,000 $400,000 $500,000 $600,000 $700,000 f(x) = 104.85 x + 33171.48 East South Central Region Square Feet Listing Price

Median Housing Price Prediction Model for D.M. Pan National Real Estate Company 4 For every 100 square feet, the house’s listing price should increase by $10,485. This can be proved by using the regression equation and multiplying 104.85 by 100. When using the regression equation, the best range would be between roughly 1,600 to 5,800. Plugging in square footage outside this range wouldn’t be very beneficial due to not having data to relate the answer to. When looking at the graph, we can compare a home of 1,600 square feet to a known value of 1,663 square feet. At 1,663 square feet, the house is listed at $250,300. It’s above the trend line but is still useful when comparing. Inputting 1,600 into our equation gives us 104.85(1600) + 33171 = $200,931. It’s pretty close to the known value of a house listed with 1,663 square feet.