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
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
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
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Step-by-step explanation:
Answer:
8x - 4y + 12
Step-by-step explanation:
-2(-4x + 2y - 6)
(-2)(-4x) + (-2)(2y) + (-2)(-6)
(2 * 4x) - (2 * 2y) + (2 * 6)
8x - 4y + 12
Answer:
X=67
Step-by-step explanation:
x-22+135=180 (180 because that line is a straight line that was intersected and a straight line has a degree of 180)
x-22+135=180
x+113=180 (combine like terms)
x=67 (combine like terms again)
Answer:
135
Step-by-step explanation:
135+45=180