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The article "technology,productivity and Indrustry structure inculded the accompanying data:

x= 2024,5038,905,3572,1157,327,378,191
y=1.90,3.96,2.44,.88,.37,-.90,.49,1.01

x=research and development expenditure
y=growth rate for eight different indrustries

a.calculate r
b.calculate r2 (r-squared) and interpret it
c. find the line of best fit
d.can the regression equation be used for predictions?

any help would be greatly appreciated! :)

2007-04-30 05:15:55 · 3 answers · asked by zack g 1 in Science & Mathematics Mathematics

btw, where it has the x and y values..im noticing that you have to point the cursor over the line because its not showing all of the data values for x and y. thanks

2007-04-30 05:17:33 · update #1

3 answers

A) r = 0.682006104

B) r² = 0.4651323259

46.5% of the change in one variable, x, is explained by a change in the related variable, y.

C) y = [5.7506488 x 10^(-4)] x + 0.2917147652

D) Yes, presuming the predictions are not extrapolated (ie, predicting outside the range of the variable or above or below the highest/lowest data point, etc) but keep in mind that because our correlation coefficient r² isn't very large and therefore probably isn't the best predictor because the line of best fit isn't too good at predicting error. So yes, it CAN, but it probably shouldn't be used to make predictions.

2007-04-30 17:35:23 · answer #1 · answered by Chris H 4 · 0 0

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2016-12-28 05:01:07 · answer #2 · answered by genevie 3 · 0 0

|r| = 0.682006104
0.9 < |r| ≤ 1 is considered a good fit
r^2 = 0.465132326
. . .not the best fit in the world. lousy, in fact . . .
y = 0.291714765 + 0.000575065x
You can use the trend line for a "general feel", but the fit is not good enough for reliable prediction.

2007-04-30 17:38:21 · answer #3 · answered by Helmut 7 · 0 1

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