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3 years ago

Pls help with my geometry!(question 3)

Mathematics

1 answer:

diamong [38]3 years ago

7 0

It’s either 30° or 45° bc of the quality I can’t really see, the trick is look at the corner and see if it’s a right angle, and every right angle is 90° if the line is straight across, it’s 45° if it’s uneven, it’s 30°

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Suppose an isosceles triangle abc has a=pi/4 and b=c=4. What is the length of a^2?

Zanzabum

The law of cosines states that, if $\alpha$ is the angle between sides b and c,

$a^2 = b^2+c^2-2bc\cos(\alpha)$

So, plugging our values, we have

$a^2 = 16+16-2\cdot 4\cdot 4\cdot\cos\left(\dfrac{\pi}{4}\right)$

This is equal to

$a^2 = 32-32\cdot\dfrac{\sqrt{2}}{2} = 32-16\sqrt{2}$

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3 years ago

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3 years ago

Please help. i will mark you brainleist

djverab [1.8K]

Answer:

w = 1/8t

Step-by-step explanation:

So this is basically saying that for every 1 second that passed, 8 oz of water drip steadily into the bucket which can be expressed like this:

8w = t

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3 years ago

Can you choose any two distinct points on a line to calculate the slope? True or False?

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3 years ago

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The body temperatures of adults are normally distributed with a mean of 98.6degrees° F and a standard deviation of 0.60degrees°

Schach [20]

Answer:

97.72% probability that their mean body temperature is greater than 98.4degrees° F.

Step-by-step explanation:

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

Normal probability distribution:

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$