You estimated a regression with the following output. Source | SS df MS Number of obs = 246 -------------+---------------------------------- F(1, 244) = 16642.70 Model | 187647307 1 187647307 Prob > F = 0.0000 Residual | 2751112.55 244 11275.0514 R-squared = 0.9856 -------------+---------------------------------- Adj R-squared = 0.9855 Total | 190398419 245 777136.405 Root MSE = 106.18 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 13.79687 .106947 129.01 0.000 13.58621 14.00753 _cons | 17.60822 9.208341 1.91 0.057 -.5297613 35.7462 ------------------------------------------------------------------------------ Which of the following is the estimated regression line? Group of answer choices a Y = 0.11 + 9.21*X b Y = 9.21 + 0.11*X c Y = 17.61 + 13.80*X d Y = 13.80 + 17.61*X
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.
You estimated a regression with the following output.
Source | SS df MS Number of obs = 246
-------------+---------------------------------- F(1, 244) = 16642.70
Model | 187647307 1 187647307 Prob > F = 0.0000
Residual | 2751112.55 244 11275.0514 R-squared = 0.9856
-------------+---------------------------------- Adj R-squared = 0.9855
Total | 190398419 245 777136.405 Root MSE = 106.18
------------------------------------------------------------------------------
Y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
X | 13.79687 .106947 129.01 0.000 13.58621 14.00753
_cons | 17.60822 9.208341 1.91 0.057 -.5297613 35.7462
------------------------------------------------------------------------------
Which of the following is the estimated regression line?
a Y = 0.11 + 9.21*X
b Y = 9.21 + 0.11*X
c Y = 17.61 + 13.80*X
d Y = 13.80 + 17.61*X
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