Consider an estimated regression explaining the salaries of CEOS(in millions of dollars) in terms of annual fırm sales (in millions of dollars), return on equity (roe in percentage form), and return on fırm's stock (ros, in percentage form) : log(salary) = 4.32 + 0.018sales + 0.0174roe + 0.00024ros How would you interpret the estimated coefficient of sales ? When sales increase by 1 million dollars, CEOS' salary is expected to increase by 0.018%. When sales increase by 1 million dollars, CEOS' salary is expected to increase by 1.8%. When sales increase by 1%, CEOS' salary is expected to increase 0.18%. When sales increase by 100%, CEOS' salary is expected to increase 0.18%.
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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