It is necessary to imagine the sum of the areas between each z-score and the average.
Given as the ratio of the area under the normal curve between two z-scores, both above average.
The Z score accurately measures the number of standard deviations above or below the mean of the data points.
The formula for calculating the z-score is
z = (data points – mean) / (standard deviation).
It is also expressed as z = (x-μ) / σ.
- A positive z-score indicates that the data points are above average.
- A negative z-score indicates that the data points are below average.
- A z-score close to 0 means that the data points are close to average.
- The normal curve is symmetric with respect to the mean and needs to be investigated.
Therefore, to find the percentage of the area under the normal curve between two z-scores, both above the mean, you need to look at the sum of the areas between the z-score and the mean.
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We need to use Law of sine.
sin A/a = sin C/c
sin A/|CB| = sin C/|AB|
sin A/14 = sin(118⁰)/ 20
sin A = (14*sin(118⁰))/ 20
A=arcsin((14*sin(118⁰))/ 20) ≈ 38⁰
9514 1404 393
Answer:
D. y=2x+6
Step-by-step explanation:
The line cannot intersect the parabola if it has a y-intercept greater than 5 and a suitable slope. The only sensible answer choice is ...
y = 2x +6
Answer:
The center/ mean will almost be equal, and the variability of simulation B will be higher than the variability of simulation A.
Step-by-step explanation:
Solution
Normally, a distribution sample is mostly affected by sample size.
As a rule, sampling error decreases by half by increasing the sample size four times.
In this case, B sample is 2 times higher the A sample size.
Now, the Mean sampling error is affected and is not higher for A.
But it's sample is huge for this, Thus, they are almost equal
Variability of simulation decreases with increase in number of trials. A has less variability.
With increase number of trials, variability of simulation decreases, so A has less variability.
A, b, d. Dilation is NOT <span>an </span><span>isometry</span>
