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astra-53 [7]
3 years ago
7

How to solve this question

Mathematics
1 answer:
VMariaS [17]3 years ago
5 0
<span>The variance method is as follows.

-Sum the squares of the values in data set, and then divide by the number of values in data set
- From that, subtract the square of the mean (add all values and divide by number of values in the data set)

Our variance is

<span>\displaystyle\sigma^2 = \frac{2^2 + 5^2 + m^2}{3} - \left(\frac{2 + 5 + m}{3}\right)^2

Since variance has to be 14, we set \sigma^2  = 14 and solve for m

14= \frac{4 + 25 + m^2}{3} - \left(\frac{7 + m}{3}\right)^2\ \Rightarrow \\ \\&#10;14 = \frac{29}{3} + \frac{1}{3}m^2 - \frac{1}{9}(7+m)^2 \\ \\&#10;14 = \frac{29}{3}+ \frac{1}{3}m^2 - \frac{1}{9}(49 + 14m + m^2) \\ \\&#10;14 = \frac{29}{3}+ \frac{1}{3}m^2 - \frac{49}{9}- \frac{14}{9}m- \frac{1}{9}m^2 \\ \\&#10;0 = \frac{-88}{9}  -\frac{14}{9}m + \frac{2}{9}m^2&#10;

quadratic formula


m = \displaystyle\frac{-b \pm \sqrt{b^2 -4ac}}{2a} \\&#10;m = \frac{-(-\frac{14}{9}) \pm \sqrt{\left(-\frac{14}{9}\right)^2 - 4(2/9)(-88/9)} }{2(2/9)} \\&#10;m = \frac{\frac{14}{9} \pm \sqrt{ \frac{196}{81} + \frac{704}{81} } }{\frac{4}{9} } \\&#10;m = \frac{\frac{14}{9} \pm \sqrt{ \frac{900}{81}  } }{\frac{4}{9} } \\&#10;m = \frac{\frac{14}{9} \pm \sqrt{ \frac{100}{9}  } }{\frac{4}{9} } \\&#10;m = \frac{\frac{14}{9} \pm \frac{10}{3}  }{\frac{4}{9} } \\&#10;m = 11, -4

-4 doesnt' work as it is not a positive integer

m = 11


</span></span>
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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.

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The solutions of a quadratic equation are ​-4,9 Write a related quadratic function in factored form.
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Step-by-step explanation:

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Cara's rate of commission is 12%.

Step-by-step explanation:

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Rounding off to nearest whole number.

Commission rate = 12%

Cara's rate of commission is 12%.

Keywords: commission, subtraction

Learn more about subtraction at:

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