Question

@jim_thompson5910

Answer 1

The answer to this one is online, I just dont understand it.

Answer 2

ok let me read it over for a sec

Answer 3

Okay

Answer 4

Here's another one, the same problem, different person answering

Answer 5

sorry I'm reading this real quick to brush up on the rules to apply

http://www.mathguy.us/BySubject/Statistics/Scatterplot_Data_Re-Expression_Summary.pdf

Answer 6

Got it

Answer 7

Not got it as in I figured it out but got it as in I'll take a look :P

Answer 8

Here's the next question, I think you know how to do it

Answer 9

ok took me a bit (longer than I wanted to lol), but I figured out how they got 1.37 + 2.64x

Answer 10

ok, the first thing that tripped me up was the fact that there were 2 breaking strengths. So I decided to plot both data sets but that was a mess. So I figured "why not average them?"

I did so and got this list

Answer 11

x is the diameter (stays the same)

the y's were computed from averaging the breaking strengths. So for instance, in the first row we have 60 and 76 for the breaking strengths. Add them up and divide by 2

(60+76)/2 = 136/2 = 68

the other rows were computed the same way

Answer 12

Yeah I got that when you said average :P

Answer 13

Is that what they want me to do? And then try to streighten it by squaring or logging or square rooting etc?

Answer 14

ok great,

if you plot these points, you get this graph

Answer 15

the points seem to fall on a parabola (parabola opens upward)

so we'll use the quadratic model shown on the pdf

Answer 16

And this is with them averaged yes?

Answer 17

yes correct

Answer 18

so what you do is apply the square root function for every y value of the averaged breaking strengths to get this new list

Answer 19

the set of points generated gives this graph

Answer 20

that data set is much more linear, the regression line I get with that last data set is

y = 1.3730408959x + 2.6478064917

which is the same as

y = 2.6478064917 + 1.3730408959x

and the person just rounded to 2 decimal places (with roundoff error? not sure)

y = 2.64 + 1.37x

Answer 21

also, this page gives a good table on which method to use and which variable to transform

http://stattrek.com/regression/linear-transformation.aspx

Answer 22

anyways, once you get this



you plug in x = 25 and then evaluate. Afterwards, you square both sides to get y-hat.