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Alexandra [31]
3 years ago
8

Vicky jogged 3 1/4 miles in 1/2 hour. What was her average rate of speed in miles per hour

Mathematics
1 answer:
DochEvi [55]3 years ago
6 0
6 1/2 per hour

since he jogged 3 1/4 for half an hour, just double the number of distance to get the distance of a full hour.

3 1/4 time 2 = 6 1/2
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The answer would be 10.976. 
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Here is a list of numbers:
vladimir2022 [97]
The median is effectively the middle number, so first we need to order them from smallest to biggest, which would be:
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Therefore, the median is 3.3.

Hope this helps!
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What is 1/3 divide by 1/4?
irina1246 [14]

Answer:

1 1/3

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1/3 divided by 1/4 =

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3 years ago
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How am I supposed to know that the government is not a good idea to have a good time to time and money on what will be an important purchase of a new era of the most important things to do in the future and the other is a great way 345
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3 years ago
g If the economy improves, a certain stock stock will have a return of 23.4 percent. If the economy declines, the stock will hav
dusya [7]

Answer:

E(X) = 23.4* 0.67 -11.9*0.33= 11.759 \%

Now we can find the second central moment with this formula:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = (23.4)^2* 0.67 +(-11.9)^2*0.33= 413.5965

And the variance is given by:

Var(X) = E(X^2) - [E(X)]^2

And replacing we got:

Var(X) = 413.5965 -(11.759)^2 =275.5105

And finally the deviation would be:

Sd(X) = \sqrt{275.5105}= 16.599 \%

Step-by-step explanation:

We can define the random variable of interest X as the return from a stock and we know the following conditions:

X_1 = 23.4 , P(X_1) =0.67 represent the result if the economy improves

X_2 = -11.9 , P(X_1) =0.33 represent the result if we have a recession

We want to find the standard deviation for the returns on the stock. We need to begin finding the mean with this formula:

E(X) = \sum_{i=1}^n X_i P(X_i)

And replacing the data given we got:

E(X) = 23.4* 0.67 -11.9*0.33= 11.759 \%

Now we can find the second central moment with this formula:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = (23.4)^2* 0.67 +(-11.9)^2*0.33= 413.5965

And the variance is given by:

Var(X) = E(X^2) - [E(X)]^2

And replacing we got:

Var(X) = 413.5965 -(11.759)^2 =275.5105

And finally the deviation would be:

Sd(X) = \sqrt{275.5105}= 16.599 \%

7 0
3 years ago
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