<span>Round (x) 1 2 3 4 5
Players f(x) 256 128 64 32 16
16-256 / 5 - 1 = -240/4 = -60
</span><span>A.) −60; on average, there was a loss of 60 each round. </span>
Answer:
- 83 1/3 ft wide
- 171 2/3 ft long
Step-by-step explanation:
Let w represent the width of the area. Then 2w+5 represents the length. The perimeter is twice the sum of length and width:
P = 2(L+W)
510 = 2(2w+5 +w) . . substitute given values
255 = 3w +5 . . . . . . divide by 2
250 = 3w . . . . . . . . . subtract 5
83 1/3 = w . . . . . . . . .divide by 3; the width of the area
2w+5 = 171 2/3 . . . . the length of the area
The fenced area is 83 1/3 ft wide and 171 2/3 ft long.
Answer:
Step-by-step explanation:
2/4 × 1/4 = (2×1)/(4×4) = 2/16 = 1/8
Answer:
x=5/3 hope i helped you
Step-by-step explanation:
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 <em>μ</em> 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 <em>n</em> = 25:
- Width for <em>n</em> = 64:
![\text{Width}=2\cdot z_{\alpha/2}\cdot \frac{\sigma}{\sqrt{64}}=\frac{1}{8}\ [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%5C%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.