Answer:
1,3.5
Step-by-step explanation:
just did it in Edge
Answer:
Neither
Step-by-step explanation:
This is a linear function as opposed to an exponential function as there are no x terms in higher powers.
We will use the law of cosines
<span>side a² = b² + c² -2bc • cos(A)
</span><span>side a² = 729 + 196 -2*27*14 * cos (46)
</span><span>side a² = 925 -(756 * 0.69466)
</span>side a² = <span><span>399.83704
</span>
side a = </span><span><span><span>19.995925585
</span>
</span>
</span>
We could round that to 20
a = 20 b = 27 c =14
We can calculate a triangle's area when we know all 3 sides by using Heron's Formula
<span>area = square root (s • (s - a) • (s - b) • (s - c))
where s is the semi-perimeter </span>
semi-perimeter<span> = (side a + side b + side c) ÷ 2</span>
s = (20 + 27 + 14) / 2
s = 30.5
Now we use Heron's Formula
area = square root (s • (s - a) • (s - b) • (s - c))
area = square root (30.5 • (<span>30.5 - 20) • (</span><span>30.5 - 27) • (</span><span>30.5 - 14))</span>
area = square root (30.5 • (10.5) • (3.5) • (<span>16.5))</span>
<span>area = square root (18494.4375)
</span>
<span><span><span>area = 135.9942553934
</span>
</span>
</span>which rounds to
136 square feet
Source:
http://www.1728.org/triang.htm
Answer:
The sample consisting of 64 data values would give a greater precision.
Step-by-step explanation:
The width of a (1 - <em>α</em>)% confidence interval for population mean μ is:

So, from the formula of the width of the interval it is clear that the width is inversely proportion to the sample size (<em>n</em>).
That is, as the sample size increases the interval width would decrease and as the sample size decreases the interval width would increase.
Here it is provided that two different samples will be taken from the same population of test scores and a 95% confidence interval will be constructed for each sample to estimate the population mean.
The two sample sizes are:
<em>n</em>₁ = 25
<em>n</em>₂ = 64
The 95% confidence interval constructed using the sample of 64 values will have a smaller width than the the one constructed using the sample of 25 values.
Width for n = 25:
Width for n = 64:
![\text{Width}=2\cdot z_{\alpha/2}\cdot \frac{\sigma}{\sqrt{64}}=\frac{1}{8}\cdot [2\cdot z_{\alpha/2}\cdot \sigma]](https://tex.z-dn.net/?f=%5Ctext%7BWidth%7D%3D2%5Ccdot%20z_%7B%5Calpha%2F2%7D%5Ccdot%20%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7B64%7D%7D%3D%5Cfrac%7B1%7D%7B8%7D%5Ccdot%20%5B2%5Ccdot%20z_%7B%5Calpha%2F2%7D%5Ccdot%20%5Csigma%5D)
Thus, the sample consisting of 64 data values would give a greater precision