100 POINTS! DUE IN 10 MINS! PLEASE HURRY I'M SOOO CONFUSED! BRAINLIEST GUARANTEED WITH THANKS AND 5-STAR RATING! PLEASE HELP

*ignore the words on the top of the second picture*

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2. Now that you have represented your data graphically, it can be more easily analyzed:

A) Describe how the line of best fit and the correlation coefficient can be used to determine the correlation between the two variables on your graph.

B) Describe the type of correlation between the two variables on your graph. How do you know?

C) Does the correlation between the variables imply causation? Explain.

D) How do you calculate the residuals for a scatterplot?

E) Calculate the residuals for your scatterplot in step 2d.

F) Create a residual plot for your data.

THANK YOU SO SO SO SO SO MUCH!

Answer(s):

A) The line of best fit gives a general outlook on the data while the correlation is the exact points showcased to calculate or show for a data set or table.

B) Between the two variables it is a positive correlation because they both increase in the same direction.  Positive correlation is a relationship between two variables in which both variables move in tandem—that is, in the same direction.

C) Not really considering the fact they are both headed in the same direction.  It would if say one was increasing and the other was going in the opposite direction.

D) So, to find the residual I would subtract the predicted value from the measured value

E)

Ex: (Your first row)

9.2 - 2.23 = 6.97

^          ^          ^

Hr.    GPA    Difference

F) Look at my added gif 'residual-plot.gif' (I believe it's asking you to sketch or raw something like that).

Thank you for letting me help you! If you have any more questions, I will gladly provide the most brainiest answers.

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

E:

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!

honesty mood

step-by-step explanation: