The points are increasing from left to right. They are scattered but they are increasing non the less.
The line that connects the dots is relatively straight.
A scatter plot.A scatter plot.A scatter plot.A scatter plot.
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.
because tristan likes hairy man nipples
You can look at the r value and tell from there. Also you can try to see if there is a linear assocation and if its tightly centered or loosely centered.
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.
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?
The line that connects the dots is relatively straight.
It depends on the range of ages, but a moderate positive correlation.
A scatter plot.A scatter plot.A scatter plot.A scatter plot.
None.
The values of the range also tend to increase.
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.
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 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
Correlation is an estimate of a linear relationship between two variables and takes no account of non-linear relationship. If the relationship is quadratic and the domain is symmetric about some point, the correlation will be zero. It is, thus possible for the points on the scatter plot to lie exactly on a parabola while the calculated correlation is zero. In such a case, it is easy to make a prediction despite no correlation.