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shusha [124]
2 years ago
9

Term

Mathematics
1 answer:
abruzzese [7]2 years ago
8 0

The computer regression output includes the R-squared values, and adjusted R-squared values as well as other important values

a) The equation of the least-squares regression line is \underline {\hat y = 235 \cdot x + 10835}

b) The correlation coefficient for the sample is approximately 0.351

c) The slope gives the increase in the attendance per increase in wins

Reasons:

a) From the computer regression output, we have;

The y-intercept and the slope are given in the <em>Coef</em> column

The y-intercept = 10835

The slope = 235

The equation of the least-squares regression line is therefore

\underline {\hat y = 235 \cdot x + 10835}

b) The square of the correlation coefficient, is given in the table as R-sq = 12.29% = 0.1229

Therefore, the correlation coefficient, r = √(0.1229) ≈ 0.351

The correlation coefficient for the sample, r ≈ <u>0.351</u>

c) The slope of the least squares regression line indicates that as the number of attending increases by 235 for each increase in wins

Learn more here:

brainly.com/question/2456202

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