MATH 1300 week 5 Assignment: Project for module 5

MATH 1300 Assignment: Project for module 5

Student Name

William Penn University

MATH1300

Professor Name

Submission Date

Based on the given data uploaded, conduct a regression analysis for the variable sale price using the living area. Summarize your findings, including all regular steps for regression. Also, will you conclude that a larger house corresponds to a higher price?

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	42.569	67.953		.626	.534
	LivingArea	38.311	2.996	.879	12.787	<.001
a. Dependent Variable: SalePrice

Pred y = mx+b

Pred y = 38.11x+42.569 where x is living area, y stands for sale price

If living area is 5

Then y = 38.11 (5) + 42.569

ANOVA^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	5015683.243	1	5015683.243	163.504	<.001^b
	Residual	1472459.757	48	30676.245
	Total	6488143.000	49
a. Dependent Variable: SalePrice
b. Predictors: (Constant), LivingArea

P< 0.001 (<0.005) regression model is significant

R.sq =.773 , (0 < R.sq < 1)

77% of variation in sell price is explained by “living area” by using our model