Answer:
A: A line of best fit is is used to represents data with the equation of a straight line in order to predict the values and represent the trend between them in the most accurate visual description. The correlation is the points that are perfectly presented to display data inside a table.
B: Based on the variable given, the two variables have an increasing or what is known as a positive correlation. Positive correlations are the relationship between scatterplot points and show which direction the graph will continue to go.
C: Causation is the indication of a relationship between two events where one event is affected by the other. With the data presented in this problem, correlation wouldn't necessarily imply causation as both are going in an upward direction. The only way for it to be true is to have the correlation increase and the causation to decrease.
D: In order to find the residuals in the scatterplot, you would subtract the predicted value form the measured value
[tex]\frac{predicted value}{measured value} = residual[/tex]
E:
[tex]9.2-2.23=6.97\\19.5-3.77=15.73\\15.5-3.92=11.58\\0.7-1.11=-1.04\\21.9-3.60=18.3\\13.8-1.42=12.38[/tex]
The you would continue for the rest of the data :)
F: I can't figure out how to attach an image (Sorry! :(
Hope this Helps!
