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Semenov [28]
2 years ago
10

Miguel ran for 850 meters and then walked for 2.75 kilometers.

Mathematics
1 answer:
olga55 [171]2 years ago
4 0

Answer:

1900 meters

Step-by-step explanation:

He ran for 850 meters

Walked for 2.75 kilometers, and that's 2.75 * 1000 meters, which is 2750 meters

The total he walked more than he ran is 2750 - 850 = 1900 meters

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m∠RSW = 2x + 16; m∠WSV = 3x + 2 m∠UST = 2x; m∠VSU = m∠UST Find m∠WSV. please answer this geotemrty is really hard
stepladder [879]
Answer: 56 degree

Explanation:

2x + 16 + 3x + 2 + 2x + 2x = 180 (straight angle)

9x + 18 = 180
9x = 162
x = 162/9
x = 18

But WSV = 3x + 2

And x = 18

=> 3(18) + 2
=> 54 + 2 = 56
8 0
2 years ago
A quality control manager at an auto plant measures the paint thickness on newly painted cars. A certain part that they paint ha
Scorpion4ik [409]

Answer:

78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value

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 = 2, \sigma = 0.8, n = 100, s = \frac{0.8}{\sqrt{100}} = 0.08

What is the probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value?

This is the pvalue of Z when X = 2 + 0.1 = 2.1 subtracted by the pvalue of Z when X = 2 - 0.1 = 1.9. So

X = 2.1

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

By the Central Limit Theorem

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

Z = \frac{2.1 - 2}{0.08}

Z = 1.25

Z = 1.25 has a pvalue of 0.8944

X = 1.9

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

Z = \frac{1.9 - 2}{0.08}

Z = -1.25

Z = -1.25 has a pvalue of 0.1056

0.8944 - 0.1056 = 0.7888

78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value

8 0
2 years ago
The Masons are driving home from a trip. The function graphed models the Masons' distance from home, y, in miles, after x hours
Paha777 [63]
You have everything right. If you look, it says Y is distance from home, and X is the time they spent driving.
I took the test and made a 100%
5 0
1 year ago
Read 2 more answers
If y ∝ 1∕x and y = –2 when x = 14, find the equation that connects x and y.
crimeas [40]

C. y= -28/x

y=k/x

cross multiply

k= y×x

k = -2×14

k = -28

y = -28/x [ equation connecting x and y]

8 0
1 year ago
A piece of buttered toast falls to the floor 17 times. The toast landed buttered side up 6 times. What is the probability that t
kirza4 [7]

Step-by-step explanation:

Given that,

A piece of buttered toast falls to the floor 17 times. The toast landed buttered side up 6 times.

It means that the total number of outcomes are 17

We need to find the probability that the toast lands buttered side down. Favourable oucome is 17-6 = 11

So, probability is given by :

P(E)=\dfrac{\text{favourable outcomes}}{\text{total no of outcomes}}

P(E)=\dfrac{11}{17}

So, the  probability that the toast lands buttered side down is 11/17.

8 0
2 years ago
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