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A correlation
true.
Dose correlation is a statistical measure of the linear relation between a dose (a measure of medication) with some other variable which could be body mass of patient, or severity of ailment or length of treatment, etc.
Another name for a dependent variable is also known as a responding variable
I've included links to both these terms. Definitions from these links are given below. Correlation and regression are frequently misunderstood terms. Correlation suggests or indicates that a linear relationship may exist between two random variables, but does not indicate whether X causes Yor Y causes X. In regression, we make the assumption that X as the independent variable can be related to Y, the dependent variable and that an equation of this relationship is useful. Definitions from Wikipedia: In probability theory and statistics, correlation (often measured as a correlation coefficient) indicates the strength and direction of a linear relationship between two random variables. In statistics, regression analysis refers to techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (also called a response variable) and of one or more independent variables (also known as explanatory variables or predictors). The dependent variable in the regression equation is modeled as a function of the independent variables, corresponding parameters ("constants"), and an error term. The error term is treated as a random variable. It represents unexplained variation in the dependent variable. The parameters are estimated so as to give a "best fit" of the data. Most commonly the best fit is evaluated by using the least squares method, but other criteria have also been used.
A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.
The word correlation is defined as the interdependence of variable quantities. It can also be defined as a mutual relationship between multiple things.
Very few people will assume, given NO correlation, that there is also a casual relationship.I will assume that you meant the fallacy in assuming that if "there is no correlation between two events there is also nocausal relationship".Correlation is a measure of linear relationship. If there is a non-linear relationship it is possible for the correlation to be low. Or, in the extreme case of a relationship that is symmetric about a specific value of the explanatory variable, for the correlation to be zero.Very few people will assume, given NO correlation, that there is also a casual relationship.I will assume that you meant the fallacy in assuming that if "there is no correlation between two events there is also nocausal relationship".Correlation is a measure of linear relationship. If there is a non-linear relationship it is possible for the correlation to be low. Or, in the extreme case of a relationship that is symmetric about a specific value of the explanatory variable, for the correlation to be zero.Very few people will assume, given NO correlation, that there is also a casual relationship.I will assume that you meant the fallacy in assuming that if "there is no correlation between two events there is also nocausal relationship".Correlation is a measure of linear relationship. If there is a non-linear relationship it is possible for the correlation to be low. Or, in the extreme case of a relationship that is symmetric about a specific value of the explanatory variable, for the correlation to be zero.Very few people will assume, given NO correlation, that there is also a casual relationship.I will assume that you meant the fallacy in assuming that if "there is no correlation between two events there is also nocausal relationship".Correlation is a measure of linear relationship. If there is a non-linear relationship it is possible for the correlation to be low. Or, in the extreme case of a relationship that is symmetric about a specific value of the explanatory variable, for the correlation to be zero.
local variable
A correlation
The further the correlation coefficient is from 0 (ie the closer to ±1) the stronger the correlation.Therefore -0.75 is a stronger correlation than 0.25The strength of the correlation is dependant on the absolute value of the correlation coefficient; the sign of the correlation coefficient gives the "relative" slope of correlation line:+ve (0 to +1) means that as one variable increases the other also increases;-ve (0 to -1) means that as one variable increases the other decreases.
false
true.
Yes.The Pearson correlation coefficient ranges from -1 to 1 inclusive.The sign of the coefficient tells you the kind of correlation:positive: as one variable increases the other also increases (like y = x)negative: as one variable increases the other decreases (like y = -x)0 means no correlation |r| = 1 means perfect correlation
True! :D
Dose correlation is a statistical measure of the linear relation between a dose (a measure of medication) with some other variable which could be body mass of patient, or severity of ailment or length of treatment, etc.
That refers to a variable attached to an object - also known as a field.