Find the regression equation? XY 11 24 15 32 17 35 19 41 O A) ŷ= 2,06 +1,11x O B) ŷ= 11,238+1,309x OC) ý= 1,309 + 11,238x D) ŷ= 1,309 + 11,238x O E) ý= 1,11 + 2,06x
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.
When we want to estimate an impact of one variable on another variable at that time we use the simple regression analysis. There are two types of variables in simple regression response variable and predictor variable.If the predictor is linearly related to the response variable then the regression model is called as simple linear regression model.
Following is the general form of a simple linear regression model:
Here, Y is the dependent (response) variable
X is the independent (predictor) variable
is the intercept indicating Y value when the predictor is zero
is the coefficient of predictor.Which indicates the contribution of independent variable in predicting the dependent variable.
e is the residual indicating the difference between the actual and fitted response value.
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