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kozerog [31]
3 years ago
10

7+q+4=4+7+q What property?

Mathematics
1 answer:
posledela3 years ago
7 0

Answer:

Commutative Property of Addition

Step-by-step explanation:

This is because the commutative property of addition and multiplication is

a+b=b+a\\a*b=b*a

and as an example

5+9=14 \\9+5=14\\10*6=60\\6*10=60

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When do we use = and when do we use ~
kati45 [8]
When we use this = it means it is the exact
answer
When we use ≈ it means it is an estimated answer and not the exact answer Example 12.4684729572974729758328 ≈ 12
4 0
4 years ago
Please Help <br><br><br><br> …………………..
Minchanka [31]

Answer:

  u = 22

Step-by-step explanation:

The triangles are congruent by SAS, so HI = JI.

  2u = u +22

  u = 22 . . . . . . . subtract u from both sides

5 0
2 years ago
Please help me!<br><br> Solve for x<br><br> 4−(2x+4)=5
Helga [31]
<span>4−(2x+4)=5
4 - 2x - 4 = 5
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5 0
4 years ago
Read 2 more answers
A box of pens and rubbers is divided equally into two bags.
lesya [120]

Answer:

my answer is 3:5

Step-by-step explanation:

sana makatulong yan

3 0
2 years ago
A roll of steel is manufactured on a processing line. The anticipated number of defects in a 10-foot segment of this roll is two
Vikentia [17]

Answer:

the probability of no defects in 10 feet of steel = 0.1353

Step-by-step explanation:

GIven that:

A roll of steel is manufactured on a processing line. The anticipated number of defects in a 10-foot segment of this roll is two.

Let consider β to be the average value for defecting

So;

β = 2

Assuming Y to be the random variable which signifies the anticipated number of defects in a 10-foot segment of this roll.

Thus, y follows a poisson distribution as number of defect is infinite with the average value of β = 2

i.e

Y \sim P( \beta = 2)

the probability mass function can be represented as follows:

\mathtt{P(y) = \dfrac{e^{- \beta} \ \beta^ \ y}{y!}}

where;

y =  0,1,2,3 ...

Hence,  the probability of no defects in 10 feet of steel

y = 0

\mathtt{P(y =0) = \dfrac{e^{- 2} \ 2^ \ 0}{0!}}

\mathtt{P(y =0) = \dfrac{0.1353  \times 1}{1}}

P(y =0) = 0.1353

4 0
3 years ago
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