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.
Correlate means to connection one thing to another in terms of how they relate to one another. For example one could write a paper to correlate how dropping out of school leads to working jobs that do not pay well.
There isn't any correlation between gathering wealth and IQ. Many factors are involved on becoming rich and keeping themselves rich. If it was true, IQ and wealth involved, rich men would not lose their wealth never. Desire of success and power leads many persons with a medium IQ to become rich.
A correlation is the relationship between two variables.Correlations are described as either weak or strong, and positive or negative, however there can be a perfect correlation between variables, or no correlation between variables.It is important to determine the correlation between variables in order to know if and how strongly one variable affects another variable (if one variable changes, how will the other variable react). This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction.-1 is less than or equal to r, r is less than or equal to +1if r= +1 or -1, there is a perfect relationshipif r= 0 there is no relationship between the variables, meaning that one variable does not affect the other variable and one variable could change without any change to the other variable.a value closer to + or - 1 demonstrates a strong relationship, while a value closer to 0 demonstrates a weak relationship.a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases.* * * * *Mostly a very good answer but ...It is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis.Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
True.
event B has something in common with event A
event B has something in common with event A
Event B has something in common with Event A.
event B has something in common with event A
The Matthew correlation coefficient considers true and false positives and negatives. The specificity correlation only considers the true classes or rejections.
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.
True
true
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.
Yes, it is true that the location of the earth's surface is directly above the focus of an earthquake is the epicenter a close correlation exists between epicenters and the plate boundaries.
True , it would have been false only if it was mentioned no relationship . But as it mentions linear it is true.
No, that is not a causative correlation.