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zalisa [80]
3 years ago
8

The exchange rate of 2 USD to Euros is 1.8. How many Euros is $34 USD? Round to 1 decimal place.

Mathematics
1 answer:
tensa zangetsu [6.8K]3 years ago
5 0

Answer:

30.6 euros

Step-by-step explanation:

Set up a proportion: 2/1.8=34/x

2x=61.2

x=30.6

Therefore, 30.6 euros

I hope this helped and have a good rest of your day!

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Step-by-step explanation:

believe it or not, the area of any triangle is

baseline × height / 2

we have here 2 triangles, both with the same baseline (8 cm), but with 2 different heights : 6.5 cm and 4.6 cm.

so, their areas are

8 × 6.5 / 2 = 4 × 6.5 = 26 cm²

8 × 4.6 / 2 = 4 × 4.6 = 18.4 cm²

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26 + 18.4 = 44.4 cm²

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Yousuf needs 7 4/9 yards of fabric to make blanket for his mom for Mother’s Day. He found 3 1/3 yards of pink fabric. How much m
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Decide if each statement about the expression 7f + 15 - 2g is true or false.
d1i1m1o1n [39]

Answer:

<h3>             FALSE</h3>

Step-by-step explanation:

The  statement "The expression contains 2 terms." is false because the expression contains 3 terms:  7f, 15 and -2g

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2 years ago
A sample of 100 cars driving on a freeway during a morning commute was drawn, and the number of occupants in each car was record
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Answer:

E(X)=1*0.74 +2*0.1 +3*0.11+ 4*0.03 +5*0.02=1.49  

Var(X)=E(X^2)-[E(X)]^2 =3.11-(1.49)^2 =0.8899  

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Step-by-step explanation:

For this case we have the following data given:

X      1    2    3    4    5

F     74   10  11    3    2

The total number of values are 100, so then we can find the empirical probability dividing the frequency by 100 and we got the followin distribution:

X          1          2        3         4          5

P(X)     0.74   0.10   0.11    0.03    0.02

Previous concepts

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".  

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).  

And the standard deviation of a random variable X is just the square root of the variance.  

Solution to the problem

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=1*0.74 +2*0.1 +3*0.11+ 4*0.03 +5*0.02=1.49  

In order to find the standard deviation we need to find first the second moment, given by :  

E(X^2)=\sum_{i=1}^n X^2_i P(X_i)  

And using the formula we got:  

E(X^2)=1^2 *0.74 +2^2 *0.1 +3^2 *0.11 +4^2 0.03 +5^2 *0.02=3.11  

Then we can find the variance with the following formula:  

Var(X)=E(X^2)-[E(X)]^2 =3.11-(1.49)^2 =0.8899  

And then the standard deviation would be given by:  

Sd(X)=\sqrt{Var(X)}=\sqrt{0.8899}=0.943  

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Answer:

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