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posledela
3 years ago
7

Is this right, can someone please explain so?

Mathematics
1 answer:
Orlov [11]3 years ago
6 0
You have to turn them in to the lowest common denominator

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An office remodeling job takes 5 & 1/2 days to complete. Before working
Oksana_A [137]

Answer: The percent of the estimated time is the actual time is about 14%.

Step-by-step explanation:

As per given,

Actual time of completing the job = 5\dfrac{1}{2}\text{ days}=\dfrac{11}{2}\text{ days}

Estimated time for completing the job = 4\dfrac{3}{4}\ \text{days}=\dfrac{19}{4}\ \text{days}

The percentage error is given by:-

\%\text{ error}= \dfrac{|\text{Estimated-Actual}|}{\text{Actual}}\times100

=\dfrac{|\dfrac{19}{4}-\dfrac{11}{2}|}{\dfrac{11}{2}}\times100\\\\\\=\dfrac{|\dfrac{19-22}{4}|}{\dfrac{11}{2}}\times100\\\\\\=\dfrac{|\dfrac{-3}{4}|}{\dfrac{11}{2}}\times100\\\\\\=\dfrac{\dfrac{3}{4}}{\dfrac{11}{2}}\times100\\\\\\=\dfrac{3\times2}{11\times4}\times100\\\\\approx14\%

The percent of the estimated time is the actual time is about 14%.

3 0
3 years ago
According to Greg, perfect cherry pies have a ratio of 210 cherries to 3 pies
Mnenie [13.5K]

630 cherries

You can setup a ratio using \frac{210}{3}=\frac{x}{9} and solve for x by multiplying 210*9 and dividing by 3 to get 630 cherries.

6 0
2 years ago
How to graph 5x-5y=20
myrzilka [38]
First you have to solve for x and y and when you have you points then plot them
6 0
3 years ago
A 16- ounce bottle of shampoo costs 4.69 what is the price per ounce rounded to the nearest cent
tester [92]

Answer:

0.29

Step-by-step explanation:

divide 4.69 by 16

this answer should give you 0.29

7 0
3 years ago
Read 2 more answers
Conditional Distribution, Marginal Distribution, Joint Distribution. <br> What’s the difference?
lutik1710 [3]

Explanation:

Marginal distribution: This distribution gives the probability for each possible value of the Random variable ignoring other random variables. Basically, the values of other variables is not considered in the marginal distribution, they can be any value possible. For example, if you have two variables X and Y, the probability of X being equal to a value, lets say, 4, contemplates every possible scenario where X is equal to 4, independently of the value Y has taken. If you want the probability of a dice being a multiple of 3, you are interested that the dice is either 3 or 6, but you dont care if the dice is even or odd.

Conditional distribution: This distribution contrasts from the previous one in the sense that we are restricting the universe of events to specific condition for other variable, making a modification of our marginal results. If we know that throwing a dice will give us a result higher than 2, then to in order to calculate the probability of the dice being a multiple of 3 using that condition, we have two favourable cases (3 and 6) from 4 total possible results (3,4,5 and 6) discarding the impossible values (1 and 2) from this universe since they dont match the condition given (note that the restrictions given can also reduce the total of favourable cases).

The joint distribution calculates the probabilities for two different events (related to two different random variables) occuring simultaneously. If we want to calculate the joint probability of a dice being multiple of 3 and greater than 2 at the same time, our possible cases in this case are 3 and 6 from 6 possible results. We are not discarding 1 or 2 as possible results because we are not assuming, that the dice is greater than 2, that is another condition that we should met in the combination of events.

3 0
3 years ago
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