Interesting question. Does that mean near the end of humanity?
Solution 1:
10^10 = 1,000,000,000
10^12 = 100,000,000,000
100,000,000,000/1,000,000,000 = 100 trees per person
Solution 2:
10^12 / 10^10 --- 10^10 / 10^10
10^2/1 = 10^2 = 100 trees per person
Answer:
A. The reflection preserves the side lengths and angles of triangle . The dilation preserves angles but not side lengths.
Step-by-step explanation:
Reflection is a rigid transformation. It preserves both angles and side lengths. Dilation preserves angles, but changes all lengths by the same scale factor.
<h3>Application</h3>
The described triangle was subject to reflection, which preserves angles and lengths. It was also subject to dilation, which preserves angles, but not lengths.
The appropriate description is that of choice A.
<h3>Explanation:</h3>
1. PQ║TS, PQ ≅ TS, PT and QS are transversals to the parallel lines . . . given
2. ∠P ≅ ∠T . . . alternate interior angles at PT
3. ∠Q ≅ ∠S . . . alternate interior angles at QS
4. ΔPQR ≅ ΔTSR . . . ASA postulate
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You can use any pair of angles together with the sides PQ and TS. If you use the vertical angles and one of ∠T or ∠S, then you must invoke the AAS postulate for congruence, as the side is not between the two angles.
The statement that 99% of all confidence intervals with a 99% confidence level should contain the population parameter of interest is false.
A confidence interval (CI) is essentially a range of estimates for an unknown parameter in frequentist statistics. The most frequent confidence level is 95%, but other levels, such 90% or 99%, are infrequently used for generating confidence intervals.
The confidence level is a measurement of the proportion of long-term associated CIs that include the parameter's true value. This is closely related to the moment-based estimate approach.
In a straightforward illustration, when the population mean is the quantity that needs to be estimated, the sample mean is a straightforward estimate. The population variance can also be calculated using the sample variance. Using the sample mean and the true mean's probability.
Hence we can generally infer that the given statement is false.
To learn more about confidence intervals visit:
brainly.com/question/24131141
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