Question

The table represents data collected on the time spent studying
Part 1: Create a scatter plot with the predicted line of best fit drawn on it. Determine the type of correlation (if any), and predict the model that will be used.
Part 2: Find the line of best fit for the data either by hand or using technology. Explain your method. Find the predicted score for each time listed in the table.

Answer 1

Part 3: Find the residuals, and decide if your model is a good fit. Explain your method. (If your model is not a good fit, complete Part 2 again with a different set of points or choose a different model.)

Answer 2

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

Answer 3

Did you try part 1 at least?

Answer 4

JUst plot the points according to your data, and judge it it looks positively or negatively correlated

Answer 5

I already did part 1 but 2 is throwing me off

Answer 6

Are you using technology or doing it by hand?

Answer 7

by hand

Answer 8

Oh dear lol. It is very tedious to do this by hand if you have more than 4 points.

Answer 9

I already got an equation for the line

Answer 10

So are you trying to find the predicted scores now?

Answer 11

yes but I don't know what it means by Find the predicted score for each time listed in the table

Answer 12

what you have is a line equation, of the form y = ax+b. Now, what you do, is take the x-values from your table (thhe time spent studying), and plug in those x-values into the equation to find the y value (this is the predicted y-value)

Answer 13

And I do that for every single one?

Answer 14

The point of this is to see if your line is determining if your line is good at predicting the grade you get, given a certain time you studied. (Because this would allow you to "predict" which grade you might get given a time of studying not given in your table)

Answer 15

Yes for every point. Because you will need this for part 3.

Answer 16

my equation is y = 0.965x + 45.547 does that work?

Answer 17

hm I didn't get that one. I used technology and it gave
y = 0.9298x - 39.0438

Answer 18

hm no that doesnt look right lol. I think I missed a point lol one sec

Answer 19

my equation works when you plug in the x

Answer 20

yes you're right lol. I accidentally switched my inputs into the program. It's good :)

Answer 21

so I plug the x in the quation for all the inputs then what do I do for c

Answer 22

Then the residual is going to be the actual y-value from your table, subtracted from the predicted y-alue you calculated in part 2.

residual = (actual y value) - (predicted y value)

Answer 23

you are seriously my new bestfriend lol

Answer 24

lol :)

Answer 25

just one last thing,when you plug in 60 in the equation you get 103..so do I just put a 100

Answer 26

no just keep it as 103. You can get values that don't make physical sense in residuals, but that's how stats works lol

Answer 27

you teach better than my teacher lol thank you so much

Answer 28

lol! awesome