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Vsevolod [243]
3 years ago
11

Write an expression without exponent that is equivalent to 2 to 3rd power nd 4 to the 3rd power

Mathematics
2 answers:
attashe74 [19]3 years ago
8 0

Answer:

2 to the 3rd power,

2*2*2

4 to the 3rd power,

4*4*4

Step-by-step explanation:

The "3rd power" means how many times the number given to it would be multiplied. Aka, 2 to the 4th power would mean 2 times 2 times 2 times 2, (2 four times).

navik [9.2K]3 years ago
4 0
4 to the 3 power
4*4*4
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The mean height of the students in Marta's class is 60 in. There are 18 students in her class. Write and Solve and equation to f
Mashcka [7]

Solution: Let x be the height of a student in Marta's class.

The mean height of 18 students in Marta's class is 60 inches

We know that:

Mean = \frac{\sum x_{i}}{n}

60 = \frac{\sum x_{i}}{18}

60 \times 18 = \sum x_{i}

\sum x_{i} = 1080

Therefore, the total measure of all 18 student's heights is 1080 inches


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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
makkiz [27]

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  

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

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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Step-by-step explanation:

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