Some people will give the answer "correlation". But that is not correct for the following reason:
Consider the coordinates of a circle. There is obviously a very strong relationship between the x coordinate and the y coordinate. The correlation between the two is not just small, but 0.
The correlation between two variables is a measure of the linear relationship between them. But there can be non-linear relationships which will not necessarily be reflected by any correlation.
Correlation * * * * * That is simply not true. Consider the coordinates of a circle. There is obviously a very strong relationship between the x coordinate and the y coordinate. But the correlation is not just small, but 0. The correlation between two variables is a measure of the linear relationship between them. But there can be non-linear relationships which will not necessarily be reflected by any correlation.
so you know the relationship between the 2 variables
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Viewing the data is an easy way to see some of their characteristics such as trends, seasonality, outliers, relationship between variables (linear, quadratic, power etc).
A measure of association. You might be thinking of the correlation coefficient in particular.
Correlation
A diagram that shows how two variables are related is called a "scatter plot." It is a visual representation of the relationship between the two variables, often used to identify patterns or trends in the data.
graph is a quick picture of relationship between two variables
A scatter plot.
Correlation * * * * * That is simply not true. Consider the coordinates of a circle. There is obviously a very strong relationship between the x coordinate and the y coordinate. But the correlation is not just small, but 0. The correlation between two variables is a measure of the linear relationship between them. But there can be non-linear relationships which will not necessarily be reflected by any correlation.
so you know the relationship between the 2 variables
Sociologists often use scatter plots to visually represent the relationship between two variables. This graphical tool helps quickly identify patterns and trends in the data, showing the strength and direction of the relationship between the variables.
The explanation of data is called a theory.
Line Graph
Correlational surveys involve measuring the relationship between two or more variables without manipulating them. By collecting data on these variables from a sample of participants, researchers can determine the extent to which changes in one variable are associated with changes in another, providing insight into potential patterns or connections between the variables.
The types of variables according to functional relationship are independent variables and dependent variables. Independent variables are inputs that are manipulated or controlled in an experiment, while dependent variables are the outputs that are affected by changes in the independent variables.
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