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3241004551 [841]
2 years ago
9

7 1/2 as a fraction greater than 1

Mathematics
1 answer:
9966 [12]2 years ago
3 0

Answer:

yes 15/2

Step-by-step explanation:

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In a population of 271 Dd parrots, predators kill 55. What is the approximate fitness of the genotype?
MissTica

Answer:

60%

Step-by-step explanation:

well i domt really know how to explain it ngl

7 0
3 years ago
Helene spends 12% of her budget on transportation expenses.Write this percent as a fraction and as a decimal.
topjm [15]
Decimal is 0.12 and fraction is 12/100

4 0
3 years ago
Which of the following could be the perimeter of a rectangle with an area of 16 square inches?
Butoxors [25]

no doubt it's 16 inches

8 0
3 years ago
Turn 276% into a mixed number
AlladinOne [14]
Mixed number is (wholenumber)+(properfraction)
a proper fraction is a/b where a<b and b≠0

so

percent means parts out of 100
x%=x/100

so
276%=
276/100=
200/100+76/100=
2+76/100=
2+38/50=
2+19/25

2 and 19/25
6 0
3 years ago
In the university library elevator there is a sign indicating a 16-person limit as well as a weight limit of 2750 pounds. Suppos
Alona [7]

Answer:

0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit

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 normally distributed samples are 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 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.

If n variables are added, the mean is n\mu and the standard deviation is s = \sqrt{n}\sigma

In this problem:

n = 16, \mu = 160*16 = 2560, s = \sqrt{16}*27 = 108

What is the probability that the random sample of 16 people in the elevator will exceed the weight limit?

This is 1 subtracted by the pvalue of Z when X = 2750. So

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

By the Central Limit Theorem

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

Z = \frac{2750 - 2560}{108}

Z = 1.76

Z = 1.76 has a pvalue of 0.961

1 - 0.961 = 0.039

0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit

7 0
3 years ago
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