Interpret the results of this regression hypothesis test.
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Linear Regression Analysis
The housing market is no stranger to trends and how those trends affect every aspect of that market. The trends are common factors that occur over a time period and that element is what regression and the trend method focus on. Trends are ever changing and this must be accounted for within the data that is tested. In this paper Team B will assess data concerning trends within the pricing of homes. This pricing is based on the relationship between the distance from a city center to a rural area and how that affects the prices. We have seen in the past papers that the prices rise the further a house is from a city's center. Here we will develop a hypothesis and then test that hypothesis using linear regression analysis.
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Solution Summary
The solution interprets the results of a regression hypothesis test.
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Regression Interpretation:
From the fitted Line Plot of Price vs Distance as shown in the following graph, it is clear that the Price and Distance from the City Center are in inverse relationship.
Regression Analysis: Price versus Distance
The regression equation is
Price = 270 - 3.35 Distance
Predictor Coef SE Coef T P
Constant 270.17 13.76 19.63 0.000
Distance -3.3540 0.8931 -3.76 0.000
S = 44.3919 R-Sq = 12.0% R-Sq(adj) = 11.2%
Analysis of Variance
Source DF SS MS F P
Regression 1 ...
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