Answer:
it aproximatley 7.937 rounded to the nearest tenth its 7.9
Step-by-step explanation:
Answer:
The proportions differ from those reported in the survey.
Step-by-step explanation:
The Chi-square goodness of fit test would be used to determine whether the proportions differ from those reported in the survey.
The hypothesis for the test can be defined as follows:
<em>H</em>₀: The proportions does not differ from those reported in the survey.
<em>Hₐ</em>: The proportions differ from those reported in the survey.
Assume that the significance level of the test is, α = 0.01.
The Chi-square test statistic is given by:

Consider the Excel sheet provided.
The Chi-square test statistic value is 191.32.
The <em>p</em>-value of the test is:

The <em>p</em>-value of the test is very small. The null hypothesis will be rejected at 1% level of significance.
Thus, concluding that the proportions differ from those reported in the survey.
The dimension that would give the maximum area is 20.8569
<h3>How to solve for the maximum area</h3>
Let the shorter side be = x
Perimeter of the semi-circle is πx
Twice the Length of the longer side
![[70-(\pi )x -x]](https://tex.z-dn.net/?f=%5B70-%28%5Cpi%20%29x%20-x%5D)
Length = ![[70-(1+\pi )x]/2](https://tex.z-dn.net/?f=%5B70-%281%2B%5Cpi%20%29x%5D%2F2)
Total area =
area of rectangle + area of the semi-circle.
Total area =
![x[[70-(1+\pi )x]/2] + [(\pi )(x/2)^2]/2](https://tex.z-dn.net/?f=x%5B%5B70-%281%2B%5Cpi%20%29x%5D%2F2%5D%20%2B%20%5B%28%5Cpi%20%29%28x%2F2%29%5E2%5D%2F2)
When we square it we would have
![70x +[(\pi /4)-(1+\pi)]x^2](https://tex.z-dn.net/?f=70x%20%2B%5B%28%5Cpi%20%2F4%29-%281%2B%5Cpi%29%5Dx%5E2)
This gives
![70x - [3.3562]x^2](https://tex.z-dn.net/?f=70x%20-%20%5B3.3562%5Dx%5E2)
From here we divide by 2

The maximum side would be at

This gives us 20.8569
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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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