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Brilliant_brown [7]
3 years ago
8

How would I write an inequality for h and -6 equaling at least 5

Mathematics
1 answer:
Novay_Z [31]3 years ago
7 0
H - 6 (greater than or equal to) 5

It wouldn’t let me type the symbol haha
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2
ArbitrLikvidat [17]
The answer would be
Day 1 = 4 inches
Day 2 = 14 inches
Day 3 = 8 inches
4 0
3 years ago
Caroline, Colin & Sarah share some money.
Pie

Answer:

I think you mean 1/9.

If so, Sarah gets 2/9 of the money.

Step-by-step explanation:

1 = 9/9

1-(1/9)= 8/9

Colin : Sarah, altogether is 8

6 : 2

Thus, Sarah get 2/9

8 0
3 years ago
Read 2 more answers
Can someone help me with this problem? thanks!
Umnica [9.8K]

Answer:

100m^2

Step-by-step explanation:

All sides of a square are equal so 10m x 10m = 100m. The answer is 100m^2 because it is a 2D figure.

4 0
2 years ago
Help please
zloy xaker [14]
What’s the question??
7 0
3 years ago
At a large university, the mean amount spent by students for cell phone service is $58.90 per month with a standard deviation of
zhenek [66]

Answer:

2.28% probability that the mean amount of their monthly cell phone bills is more than $60

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.

In this problem, we have that:

\mu = 58.90, \sigma = 3.64, n = 44, s = \frac{3.64}{\sqrt{44}} = 0.54875

What is the probability that the mean amount of their monthly cell phone bills is more than $60?

This is 1 subtracted by the pvalue of Z when X = 60. So

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

By the Central Limit Theorem

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

Z = \frac{60 - 58.90}{0.54875}

Z = 2

Z = 2 has a pvalue of 0.9772

1 - 0.9772 = 0.0228

2.28% probability that the mean amount of their monthly cell phone bills is more than $60

4 0
3 years ago
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