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3 years ago

7 divided by 238 long division show work

Mathematics

2 answers:

sesenic [268]3 years ago

6 0

7 goes into 238 34 times right you would put 34 under 23 in 238 and 238-34=204 thats how i do it in my school hope it help:)

Aleonysh [2.5K]3 years ago

5 0

Answer:

The solution for long division of 238÷7 is 34 with remainder of 0. You may check the attached figure a to visualize step by step solution of this long division.

Step-by-step explanation:

Please check the attached figure a to visualize step by step solution of this long division.

Here is the step by step solution of 7 divided by 238.

Write the problem in long division format
Divide 23 by 7 to get 3
Multiply the quotient digit (3) by the divisor 7
Subtract 21 from 23
Bring down the next number of the dividend
Divide 28 by 7 to get 4
Multiply the quotient digit (4) by the divisor 7
Subtract 28 from 28
Remainder 0

Hence, The solution for long division of 238÷7 is 34 with remainder of 0. Please see the attached figure a to visualize step by step solution of this long division.

Keywords: long division, divide

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Answer:

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Step-by-step explanation:

Great question, it is always good to ask away and get rid of any doubts that you may be having.

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3 years ago

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3 years ago

The time for a visitor to read health instructions on a Web site is approximately normally distributed with a mean of 10 minutes

klio [65]

Answer:

a) The mean is 10 and the variance is 0.0625.

b) 0.6826 = 68.26% probability that the mean time of the visitors is within 15 seconds of 10 minutes.

c) 10.58 minutes.

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

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Normally distributed with a mean of 10 minutes and a standard deviation of 2 minutes.

This means that $\mu = 10, \sigma = 2$

Suppose 64 visitors independently view the site.

This means that $n = 64, = \frac{2}{\sqrt{64}} = 0.25$

a. The expected value and the variance of the mean time of the visitors.

Using the Central Limit Theorem, mean of 10 and variance of (0.25)^2 = 0.0625.

b. The probability that the mean time of the visitors is within 15 seconds of 10 minutes.

15 seconds = 15/60 = 0.25 minutes, so between 9.75 and 10.25 seconds, which is the p-value of Z when X = 10.25 subtracted by the p-value of Z when X = 9.75.

X = 10.25

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

By the Central Limit Theorem

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