A positive correlation is where the data has an increasing pattern. As X increases, Y also increases.
POSITIVE CORRELATION IS CORRELATION THAT IS LINKED. REPHRAISED IT MEANS:POSITIVE CORRELATION IS CORRELATION IN WHICH BOTH AXIS ARE LINKED. SO IN SOME EXTREME CASES IT WOULD BE, (X=Y).BUT ON WITH THE QUESTION ANSWERING.HERE ARE A FEW EXAMPLES OF POSITIVE CORRELATION:1. THE AMOUNT OF COFFEE DRUNK AND THE NUMBER OF HOURS STAYED AWAKE.2. THE NUMBER OF PEOPLE FLYING TO AUSTRALIA AND THE NUMBER OF PLANES FLYING TO AUSTRALIA.THESE CAN EASILY BE CHANGED INTO SCATTER DIAGRAMS. IF YOU WANT TO KNOW MORE ABOUT POSITIVE CORRELATION THAN COME TO HAWLEY PLACE SCHOOL nd ask to see mr freeman.OTHER EXAMPLES OF POSITIVE CORRELATION IS THAT1.MARKS OF STUDENT AND HIS QUOTIENT. IN THIS CASE THERE IS POSITIVE CORRELATION BETWEEN THESE TWO VARIABLE.ON OTHER HAND IN SOME OTHER SITUATION "INCREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH INCREASE IN VALUE OF ANOTHER VARIABLE OR DECREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH DECREASE IN VALUE OF ANOTHER VARIABLE IS CALLED POSITIVE CORRELATION".
a. The correlation between X and Y is spurious b. X is the cause of Y c. Y is the cause of X d. A third variable is the cause of the correlation between X and Y
Corr = cov(X,Y)/[stdev(X)*stdev(Y)] Negative correlation would be when X decreases as Y increases or vice versa.
Data can be correlated (meaning there is an indication of a relationship) either positively or negatively. The datasets of two variables (x,y) which have a negative correlations, when plotted, will show a negative trend, that means with increasing values of x, there will be, generally, decreasing values of y. An example of negative correlation, would be the more hours someone exercises, the less they weigh, if weight loss is measured as a negative number and weight gain as a positive number. In this case x= hours exercised, y = final weight - original weight. For presentation purposes, we frequently define our variable to show positive correlations. As per the above example, I could have defined y = original weight - final weight, which would show a positive correlation and plot as an upward trend. It would not change the absolute value of correlation just the sign. You may check wikipedia under correlation to get more understanding.
It is implied that x increases when y decreases and conversely. There is no implication about a causal relationship.
Positive Correlation
I believe you are asking how to identify a positive or negative correlation between two variables, for which you have data. I'll call these variables x and y. Of course, you can always calculate the correlation coefficient, but you can see the correlation from a graph. An x-y graph that shows a positive trend (slope positive) indicates a positive correlation. An x-y graph that shows a negative trend (slope negative) indicates a negative correlation.
If Y increases as X increases, you are referring to a positive correlation. However, if Y falls as X increses, you have a negative correlation.
A positive correlation is where the data has an increasing pattern. As X increases, Y also increases.
Assume that you are correlating two variables x and y. If there is an increasing relationship between x and y, (that is , the graph of y=a+bx, slopes upward), the correlation coefficient is positive. Similarly, if there is a decreasing relationship, the correlation coefficient is negative. The correlation coefficient can assume values only between -1 and 1.
It means that the two variables are likely dependent. The higher the number of the positive correlation the stronger the connection.
"If y tends to increase as x increases, then the data have a positive correlation. If y tends to decrease as x increases, then the data have a negative correlation. If the points show no correlation, then the data have approximately no correlation."
Shadow is not said to, implied to, or believed to love a character in Sonic X.
Positive correlation refers to a relationship between two variables where they move in the same direction, meaning an increase in one variable is associated with an increase in the other variable. Negative correlation, on the other hand, refers to a relationship where the variables move in opposite directions, so an increase in one variable is associated with a decrease in the other variable.
POSITIVE CORRELATION IS CORRELATION THAT IS LINKED. REPHRAISED IT MEANS:POSITIVE CORRELATION IS CORRELATION IN WHICH BOTH AXIS ARE LINKED. SO IN SOME EXTREME CASES IT WOULD BE, (X=Y).BUT ON WITH THE QUESTION ANSWERING.HERE ARE A FEW EXAMPLES OF POSITIVE CORRELATION:1. THE AMOUNT OF COFFEE DRUNK AND THE NUMBER OF HOURS STAYED AWAKE.2. THE NUMBER OF PEOPLE FLYING TO AUSTRALIA AND THE NUMBER OF PLANES FLYING TO AUSTRALIA.THESE CAN EASILY BE CHANGED INTO SCATTER DIAGRAMS. IF YOU WANT TO KNOW MORE ABOUT POSITIVE CORRELATION THAN COME TO HAWLEY PLACE SCHOOL nd ask to see mr freeman.OTHER EXAMPLES OF POSITIVE CORRELATION IS THAT1.MARKS OF STUDENT AND HIS QUOTIENT. IN THIS CASE THERE IS POSITIVE CORRELATION BETWEEN THESE TWO VARIABLE.ON OTHER HAND IN SOME OTHER SITUATION "INCREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH INCREASE IN VALUE OF ANOTHER VARIABLE OR DECREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH DECREASE IN VALUE OF ANOTHER VARIABLE IS CALLED POSITIVE CORRELATION".
It implies that an increase in x is accompanied by an increase in y. And similarly, they decrease together.