With a dilation, each dimension increases by the factor. Thus, if we let the dimensions be x and y, the new dimensions are 2x and 2y.
(a): The original perimeter is 2(x+y), but the new one is 2(2x+2y). This is twice the original perimeter, so it is 18*2=36.
(b): The original area is xy, and the new one is (2x)(2y), or 4xy. This is four times the original area, or 20*4=80.
(c): As it's given that the side lengths are integers, the intended solution is most likely to divide by 2 in the perimeter to see that the sum of the side-lengths is 9 and their product is 20. Guessing/checking values for each side, we see that 4 and 5 work for the smaller rectangle. Multiplying by two, the larger one has lengths 8 and 10.
Alternatively, we set them to x and y and use the equations:
x+y=9
xy=20
Dividing by y, we see that x=20/y. Substituting, we have that y+20/y=9. Subtracting 9 and multiplying by y, we have:
y^2-9y=20
Factoring, we have (y-5)(y-4)=0. The solutions to this equation are 4 and 5, which result in x=5, y=4 or x=4, y=5 respectively. Thus, we see that 4 and 5 are the side-lengths. Note that this solution did not require the assumption that the side-lengths are integers!
Answer:
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Step-by-step explanation:jjffgjgb
Answer:
As the <em>p</em>-value is too small the null hypothesis will be rejected concluding that there is a higher proportion of people supporting the home team.
Step-by-step explanation:
The hypothesis to determine which team spectators at a football game support is:
<em>H₀</em>: There are equal proportions of people supporting the home team and the visiting team, i.e. <em>p</em>₁ = <em>p</em>₂.
<em>Hₐ</em>: There is a higher proportion of people supporting the home team than the visiting team, i.e. <em>p</em>₁ > <em>p</em>₂.
A <em>z</em>-test for difference between proportions can be used to perform the test.
The test statistic is:

Th decision rule is:
If the <em>p</em>-value of the test is less than the significance level <em>α </em>then the null hypothesis will be rejected and vice-versa.
The commonly used significance levels are 0.01, 0.05 and 0.10.
The <em>p</em>-value of the test is computed as, <em>p</em> = 0.002.
The <em>p</em>-value of the test is less than all the significance level.
Thus, the null hypothesis will be rejected at any of the three significance level.
Conclusion:
As the <em>p</em>-value is too small the null hypothesis will be rejected concluding that there is a higher proportion of people supporting the home team.