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.
They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'
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.