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3 years ago

Anybody know geometry?

Mathematics

1 answer:

Rudik [331]3 years ago

5 0

hi as a person who is taking geometry, i think i can help

Answer:

7x-3=5x+1 ->x=2

Step-by-step explanation:

to find the x, you would put both equations together like how it is shown above, then try and get x to one side

7x-3=5x+1

+3 +3

7x=5x+4

-5x -5x

2x=4

/2 /2

x=2

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A factory received a shipment of 11 hammers, and the vendor who sold the items knows there are 2 hammers in the shipment that ar

zhenek [66]

Question:

If a sample of 2 hammer is selected

(a) find the probability that all in the sample are defective.

(b) find the probability that none in the sample are defective.

Answer:

a $Pr = \frac{2}{110}$

b $Pr = \frac{72}{110}$

Step-by-step explanation:

Given

$n = 11$ --- hammers

$r = 2$ --- selection

This will be treated as selection without replacement. So, 1 will be subtracted from subsequent probabilities

Solving (a): Probability that both selection are defective.

For two selections, the probability that all are defective is:

$Pr = P(D) * P(D)$

$Pr = \frac{2}{11} * \frac{2-1}{11-1}$

$Pr = \frac{2}{11} * \frac{1}{10}$

$Pr = \frac{2}{110}$

Solving (b): Probability that none are defective.

The probability that a selection is not defective is:

$P(D') = \frac{9}{11}$

For two selections, the probability that all are not defective is:

$Pr = P(D') * P(D')$

$Pr = \frac{9}{11} * \frac{9-1}{11-1}$

$Pr = \frac{9}{11} * \frac{8}{10}$

$Pr = \frac{72}{110}$

8 0

2 years ago

Suppose that the walking step lengths of adult males are normally distributed with a mean of 2.5 feet and a standard deviation o

Mumz [18]

Answer:

0% probability that the mean of the sample taken is less than 2.2 feet.

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 establishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .