The following data were used in a regression study. Observation 1234 56 2 34577789 354 7469 6 11 (a) Develop an estimated regression equation for these data. (Round your numerical values to two decimal places.) (b) Construct a plot of the residuals. :. -2- -2 -2 -2 -4 4. 10 4 10 4 8 10 4. 10 Do the assumptions about the error term seem to be satisfied? O The plot suggests curvature in the residuals indicating that the error term assumptions are not satisfied. O The plot suggests curvature in the residuals indicating that the error term assumptions are satisfied. O The plot suggests a generally horizontal band of residual points indicating that the error term assumptions are not satisfied. O The plot suggests a funnel pattern in the residuals indicating that the error term assumptions are satisfied. O The plot suggests a funnel pattern in the residuals indicating that the error term assumptions are not satisfied.
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.
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