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const2013 [10]
3 years ago
10

Suppose that the weight (In pounds) of an airplane is a linear function of the total amount of fuel (In gallons) in its tank. Wh

en graphed, the function gives a line
with a slope of 6.3. See the figure below.
with 49 gallons of fuel in its tank, the airplane has a welght of 2308.7 pounds. What is the weight of the plane with 16 gallons of fuel in its tank?

Mathematics
1 answer:
alexira [117]3 years ago
8 0

Answer:

read the sentences. write the types of indirect characterization. seleck from spech, thoughts,

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What is the GCF of 2+18+40
vlabodo [156]
2 is the GCF of <span>2+18+40
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6 0
3 years ago
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Julia has 3 ribbons that are 12 inches each. how many 4 inch sections can she cut from the ribbon.
Ber [7]
Total length of all ribbons = 12 * 3 = 36 inch

Then, number of ribbons = 36/4 = 9

In short, Your Answer would be: 9 sections

Hope this helps!
6 0
3 years ago
The mean points obtained in an aptitude examination is 159 points with a standard deviation of 13 points. What is the probabilit
Korolek [52]

Answer:

0.4514 = 45.14% probability that the mean of the sample would differ from the population mean by less than 1 point if 60 exams are sampled

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 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 random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 159, \sigma = 13, n = 60, s = \frac{13}{\sqrt{60}} = 1.68

What is the probability that the mean of the sample would differ from the population mean by less than 1 point if 60 exams are sampled?

This is the pvalue of Z when X = 159+1 = 160 subtracted by the pvalue of Z when X = 159-1 = 158. So

X = 160

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

By the Central Limit Theorem

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

Z = \frac{160 - 159}{1.68}

Z = 0.6

Z = 0.6 has a pvalue of 0.7257

X = 150

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

Z = \frac{158 - 159}{1.68}

Z = -0.6

Z = -0.6 has a pvalue of 0.2743

0.7257 - 0.2743 = 0.4514

0.4514 = 45.14% probability that the mean of the sample would differ from the population mean by less than 1 point if 60 exams are sampled

7 0
3 years ago
What number multiples to -1 and adds to -50
koban [17]
Z: is the number

[Z*(-1)]+(-50)
(-Z)+(-50)
-Z-50

<span>I hope it helps you :)</span>
5 0
3 years ago
Ok so do I subtract 5 from x and 5 Orr am I solving wrong i don’t know this is confusing.
Aleksandr [31]

Answer:

no you dont

Step-by-step explanation:

4 0
3 years ago
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