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maxonik [38]
4 years ago
9

an electrician has 4.1 meters of wire. How much stripes 7/10m long can he cut? How much wire will he have left over?

Mathematics
2 answers:
GalinKa [24]4 years ago
7 0

From 4.1 meters wire, we can make 5 stripes with 0.6 meters wire being left.

<u>Solution:</u>

Given that, an electrician has 4.1 meters of wire.  

We have to find  

1) Number of stripes 7/10m long can he cut:

Now, we know that, number of stripes he can make =\frac{\text {available length of wire}}{\text {Length of each stripe}}=\frac{4.1}{\frac{7}{10}}

\Rightarrow \frac{4.1}{\frac{7}{10}}=4.1 \times \frac{10}{7}=\frac{41}{7}=5.857

So, he can make 5 full stripes. We have to neglect fractional value as that is not considered as stripe.

2) Measure of left over wire:

No, we know that, remaining length of wire = total wire length-used length wire  

\begin{array}{l}{\text { Length of left over wire }=4.1 \text { meters- number stripes used }\times \text {length of each stripe }} \\\\ {\text { Length of left over wire }=4.1-5 \times \frac{7}{10}=4.1-\frac{7}{2}=4.1-3.5=0.6 \text { meters }}\end{array}

So, 0.6 meters of wire is left.

ratelena [41]4 years ago
4 0

Answer:

5 such strips of \frac{7}{10}\ m can be cut and \frac{6}{10}\ m  would be left over.

Step-by-step explanation:

Given is4.1= \frac{41}{10}\ m length of a wire.

We have to cut strips of \frac{7}{10}\ m

If we factorize 41 \ by \ 7

We get 5 full and and \frac{6}{7}

Similarly , if we factorize \frac{41}{10} \ by \ \frac{7}{10}

We get full 5 \ strips and another \frac{6}{10} \ m would be left.

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The depth of a lake in cedar burg changes over time due to rain fall and evaporation this year it was 39 feet which is 25% less
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Answer:

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Step-by-step explanation:

Given as :

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Let the last year depth of lake = x feet

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3 years ago
A population has mean 187 and standard deviation 32. If a random sample of 64 observations is selected at random from this popul
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Answer:

11.51% probability that the sample average will be less than 182

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:

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By the Central Limit Theorem

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

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