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disa [49]
3 years ago
6

an electronics manufacturer has 140 capacitors, and the same number of capacitors is needed for each circuit board made. the man

ufacturer uses the capacitors to make 35 circuit boards. Identify and interpret, plot the points on a graph, and connect the points
Mathematics
1 answer:
natka813 [3]3 years ago
8 0
Let x be the number of circuit boards that can be produced and m be the number of capacitors per circuit board
y = mx
140 capacitors allowed the production of 35 boards.
140 = 35x
x = 4
No circuit boards can be made without capacitors so the line's y intercept is 0. No capacitors are used if no circuit boards are to be made so the x intercept is also 0.
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2 years ago
At a new exhibit in the Museum of Science, people are asked to choose between 94 or 220 random draws from a machine. The machine
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Answer:

0.0869 = 8.69% probability of getting more than 61% green balls.

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 normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, 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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

The machine is known to have 99 green balls and 78 red balls.

This means that p = \frac{99}{99+78} = 0.5593

Mean and standard deviation:

\mu = p = 0.5593

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.5593*0.4407}{99+78}} = 0.0373

a. Calculate the probability of getting more than 61% green balls.

This is 1 subtracted by the pvalue of Z when X = 0.61. So

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

By the Central Limit Theorem

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

Z = \frac{0.61 - 0.5593}{0.0373}

Z = 1.36

Z = 1.36 has a pvalue of 0.9131

1 - 0.9131 = 0.0869

0.0869 = 8.69% probability of getting more than 61% green balls.

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kodGreya [7K]

Step-by-step explanation:

28m+4n-12m+3

28m-12m+4n+3

16m+4n+3

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Step-by-step explanation: it is

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