If they increase or decrease exactly, then the constant of proportionality or coefficient of proportionality. If not exactly, then a correlation coefficient.
No. The ratio of consecutive values of y for equal x-intervals will be approx constant.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
Evidence that there is no correlation.
They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'
Since I am a constant, not a variable, there can be no correlation. The calculation would entail division by zero, which is not permitted.
Let me rephrase: Case 1: You have x and y variables, but the values for x is a constant (vertical line) Case 1: You have x and y variables, but the values for y is a constant (horizontal line) Result is that you have zero covariance, so a correlation coefficient can not be calculated because that would cause a division by zero. If one of your x value (Case 1) or y value (case 2) is not exactly the same as the others, then a correlation coefficient can be calculated, but does it mean anything? The correlation coefficient indicates a linear relationship between two random variables, not between a constant and a random variable.
Auto correlation is the correlation of one signal with itself. Cross correlation is the correlation of one signal with a different signal.
If they increase or decrease exactly, then the constant of proportionality or coefficient of proportionality. If not exactly, then a correlation coefficient.
positive correlation-negative correlation and no correlation
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
No. The ratio of consecutive values of y for equal x-intervals will be approx constant.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
No.
Indentation rhymes with correlation
Evidence that there is no correlation.