Correlation means that when one quantity increases, the other tends to increase as well. Causation means that the increase in one quantity CAUSES an increase in another quantity. It is a common error to assume that correlation implies causation; sometimes correlation is caused by causation, but not always. For example: let's say that the price of sugar gradually went up over the last 10 years; so did the price of cooking oil. Neither one is caused by the increase of the other; rather, they are both part of a larger tendency, namely, inflation. As another example, during the same 10-year period, the population of your country gradually increased. This is independent of the inflation; both prices and population simply tend to increase over time.
positive correlation-negative correlation and no correlation
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
No, The correlation can not be over 1. An example of a strong correlation would be .99
partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.
0
Auto correlation is the correlation of one signal with itself. Cross correlation is the correlation of one signal with a different signal.
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).
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.
No, The correlation can not be over 1. An example of a strong correlation would be .99
No. The units of the two variables in a correlation will not change the value of the correlation coefficient.
a number derived from the formula for measuring a correlation and indicating the strength and direction of a correlation
They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'