Question

Help...

Answer 1

what's the question?

Answer 2

Question 1: The table represents data collected on the time spent studying (in minutes) and the resulting test grade.
Time Spent Studying (min) 52 37 31 9 26 40 22 10 45 34 19 60
Grade on Test 95 84 72 58 77 86 72 43 90 81 62 98

Part 1: Create a scatter plot (***In Geogebra***)
Determine the type of correlation (positive, negative, no correlation):____________________________

Predict the model that will be used (Linear/ Non Linear): _______________________________________
Part 2: Use Geogebra to find the line of best fit
Write your equation here: _______________________________________________________________

What does x-represent? ___________________ What does y-represent?_______________________

Based on your equation, write the values for y below:
Time Spent Studying (min) 52 37 31 9 26 40 22 10 45 34 19 60
Grade on Test 95 84 72 58 77 86 72 43 90 81 62 98
Grade per linear model
Difference

Find the sum of the differences to calculate the residual:

Do you think you equation was a good approximate of the data? Why? Why not?

Answer 3

Yeah its a bit complicated...

Answer 4

...and you seem to have to use GeoGebra for it :/

Answer 5

I can do that part its really easy you just put it in the input box at the bottom I just don't know the coordinates to put :/

Answer 6

time is x, grade is y ....

Answer 7

Oh ok so I jut put that coordinate right next to the one on the bottom?

Answer 8

x:Time 52 37 31 9 26 40 22 10 45 34 19 60
y:Grade 95 84 72 58 77 86 72 43 90 81 62 98

use these for the scatter plot points ....

then geogebra calculates the best fit linear equation, call it y'. Use that equation to determine the predicted values ... y' is your linear prediction model.

then the residual is simply the difference between the predicted model and the observed data. y - y'

Answer 9

I got the scatter plot points and I think I know how to put it in but I don't get what you mean by the last 2 papagraphs

Answer 10

simply filling out the rows ....

row3: Grade per linear model
row4: Difference

and then; Find the sum of the differences to calculate the residual:

Answer 11

whats a residual?

Answer 12

residual ... whats left over.

the residual is simply the difference between the predicted model and the observed data. y - y'

Answer 13

you mean remainder?

Answer 14

y' predicts a value for a given x. the residual accounts for the difference between what is observed, and what is predicted.

Answer 15

oh ok I get it now

Answer 16

so how do we determine the type of correlation?

Answer 17

either by a geogebra menu ... or visually looking at the graph.

if it looks like a cat sneezed on your homework .... then there is no correlation, the slope of y' will be pretty much flat (essentially zero)

if the data seems to conform to a linear grouping, such that it all heads in an upward direction, the slope of y' will be positive ... if its downward, then y' will have a negative slope.

Answer 18

oh ok and lol