SUMWRYOUTPUT Regression Statistics Multiple A RSquare Adusted R Square 0sa2107045 Standard Eror 0.777020675 0603761129 87111.55191 Observations ANOVA df MS Signécance F 4E11 4E11 Regression Residual Total SEN01 3E08 34 E11 E:09 36 E11 Coeticients Standard Error Staf Pvalue 48909 96 Leper 9% Lower 960% Upper 9.0% 27072846 22972 Lower S% Intercept Sqft 171331.46 3.50 0.00 71934.48 270728.46 12856 71934.45 179.14 2489 720 0.00 229.72 128.56
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
A Realtor examines the factors that influence the price of a house in Arlington, Massachusetts. He collects data on recent house sales (Price) and notes each house’s square footage (Sqft) as well as its number of bedrooms (Beds) and number of bathrooms (Baths).
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