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svetlana [45]
4 years ago
10

Which statements about the composite figure are true? Check all that apply.

Mathematics
1 answer:
AnnyKZ [126]4 years ago
5 0

Where’s the answers ?

Step-by-step explanation:

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Evaluate what’s in the picture.
Anna11 [10]

Answer:

8P3 = 336

9C4 = 126

Step-by-step explanation:

8P3 = 8! ÷ 5!  =  8x7x6 = 336

9C4 = 9! ÷ (5!·4!)  =  (9x8x7x6) ÷ (4x3x2) = 126

8 0
3 years ago
You walk 2 miles from your house to the park and 4.5 miles from the park to the lake. Then you return home along a straight path
pshichka [43]
If they took the same route home itll be 13 miles
8 0
3 years ago
Read 2 more answers
Plz I REALLY NEED HELP
zimovet [89]
6inches long on the screen
3 0
3 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
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  

7 0
3 years ago
Write 4408730 in expanded form
kodGreya [7K]
4000000+400000+8000+700+30

5 0
3 years ago
Read 2 more answers
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