Look at the Table, specifically the information related to "stroke severity." What is the dependent and the independent variables? Provide an interpretation of the coefficient (coeff), standard error (SE), and p-value for temperature & previous stroke
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.
Look at the Table, specifically the information related to "stroke severity." What is the dependent and the independent variables? Provide an interpretation of the coefficient (coeff), standard error (SE), and p-value for temperature & previous stroke.
The dependent variable is a variable that changes depending on the value of another variable.
The independent variables are the variables that are manipulated by researcher to study its effect on the dependent variable.
For the first part of table, stroke severity is a dependent variable that depends on many other variables as temperature, male, previous stroke atrial fibrillation, leucocytosis and infections, thus all these variables are independent variables.
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