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777dan777 [17]
3 years ago
15

Consider the two triangles shown. Which statement is true?

Mathematics
2 answers:
dolphi86 [110]3 years ago
5 0

The answer is D. The triangles have proportional sides (the triangle on the left has sides that are 4 times that of the triangle on the left). Since the triangles have proportional sides, the angles given will also be equal. Thus, we can show their similarity through both the SSS and SAS similarities.

telo118 [61]3 years ago
3 0
Answer: D

Explanation:
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Help quick or else trouble
sasho [114]

Answer:

1/21

Step-by-step explanation:

2/7 ÷ 6 =

2/7 x 1/6 = 2/42

Simplify by dividing the numerator and denominator by 2

1/21

If my answer is incorrect, pls correct me!

If you like my answer and explanation, mark me as brainliest!

-Chetan K

7 0
3 years ago
1+2i/2+3i simplified
Aleonysh [2.5K]
8/13 + i/13 hope this helps
4 0
3 years ago
Find the slope, or rate of change:
Sedbober [7]
3/2 because the proper solution is rise over run, in this case it rises 3 & runs to the right 2
4 0
2 years ago
Annual starting salaries in a certain region of the U. S. for college graduates with an engineering major are normally distribut
defon

Answer:

0.8665 = 86.65% probability that the sample mean would be at least $39000

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean $39725 and standard deviation $7320.

This means that \mu = 39725, \sigma = 7320

Sample of 125:

This means that n = 125, s = \frac{7320}{\sqrt{125}} = 654.72

The probability that the sample mean would be at least $39000 is about?

This is 1 subtracted by the pvalue of Z when X = 39000. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{39000 - 39725}{654.72}

Z = -1.11

Z = -1.11 has a pvalue of 0.1335

1 - 0.1335 = 0.8665

0.8665 = 86.65% probability that the sample mean would be at least $39000

4 0
3 years ago
What is the expanded form of the number below?
Burka [1]
It is the first one
3 0
3 years ago
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