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
Line graph
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.
graph is a quick picture of relationship between two variables
A scatter plot.
so you know the relationship between the 2 variables
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.
Qualitative Data
The explanation of data is called a theory.
Line Graph
Line graph
It suggests that there is very little evidence of a linear relationship between the variables.
if it passes through (0,0) then it is a direct variation
Economic forecasting models predominantly use time-series data, where the values of the variables change over time.
The Correlation Coefficient computed from the sample data measures the strength and direction of a linear relationship between two variables. The symbol for the sample correlation coefficient is r. The symbol for the population correlation is p (Greek letter rho).