Can you split the name of this up somehow when you resubmit your question, so that an answerer can attempt to use the search facility on Photobucket.com?
Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.
An example of a positive correlation is: the number of cars on the road and the number of greenhouse gas emissions there are. As one of those rises, so does the other. A negative correlation is when one statistic rises causing the other to drop. Look at a few scatter plots and you will easily be able to see positive and negative correlations
you graph the points going downwards
It depends on the range of ages, but a moderate positive correlation.
Yes. * A positive correlation is when the dependant variable increases as the independent one does. * A negative correlation is when the dependant variable decreases as the independent one increases. * Perfect correlation is when all the points lie along a straight line; no correlation is when the points lie all over the place. In calculating the correlation coefficient it can have a value between -1 and 1, with 0 indication no correlation and values between 0 and ±1 showing a greater correlation until ±1 which is perfect correlation. Moderate correlation would be one of these intermediate values, eg ±0.5, which shows the points are moderately related.
A correlation exists in a scatter plot if there is a general trend in the outputs as inputs increase. If the outputs generally increase in value, then there is a positive correlation. If the outputs generally decrease in value, then there is a negative correlation.
Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.
None.
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.
An example of a positive correlation is: the number of cars on the road and the number of greenhouse gas emissions there are. As one of those rises, so does the other. A negative correlation is when one statistic rises causing the other to drop. Look at a few scatter plots and you will easily be able to see positive and negative correlations
A scatterplot with no correlation means that there is no relation between the two categories, a negative correlation means that the two categories have a relationship that as one gets greater the other gets smaller
you graph the points going downwards
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
When you have a scatter graph and you want to find the correlation of it, you draw a line from one corner to the other of the grid.Also, if the categories are to do with the same thing, then it's a positive correlation.
"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."
It depends on the range of ages, but a moderate positive correlation.
Yes. * A positive correlation is when the dependant variable increases as the independent one does. * A negative correlation is when the dependant variable decreases as the independent one increases. * Perfect correlation is when all the points lie along a straight line; no correlation is when the points lie all over the place. In calculating the correlation coefficient it can have a value between -1 and 1, with 0 indication no correlation and values between 0 and ±1 showing a greater correlation until ±1 which is perfect correlation. Moderate correlation would be one of these intermediate values, eg ±0.5, which shows the points are moderately related.