Negative association.
Yes
Positive correlation = positive association Negative correlation = negative association
both, variables can be anything
includes both positive and negative terms.
False.
Negative health is a bad thing, it shows that there is regression. Positive health on the other hand, is a good thing. It shows improvement.
It means that there is a strong positive association between changes in the two variables being studied. Positive association means that the two variables tend to increase together or decrease together. Note that there is no mention of a causal relationship between the variables.
Context language consists of words that create positive or negative associations
An association is a relationship between two or more variables where they co-occur or change together. It measures the strength and direction of the relationship between variables, indicating how one variable is affected by changes in another. Associations can be positive, negative, or neutral.
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.
No. They are unsigned, therefore all representations are positive.
False. Correlation coefficient as denoted by r, ranges from -1 to 1. Coefficient of determination, or r squared ranges from 0 to 1. I note that x,y data points that have a high negative correlation would plot with a negative trend or a negatively sloped line if a best fit regression line is determined. I note also that x,y data points with a high positive correlation would plot with a positive trend or positively sloped line if a best fit regression line is determined. The coefficient of determination for r = 0.9 and r= -0.9 would be 0.81.