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GarryVolchara [31]
2 years ago
14

Find the value of s.1s + 14 = 26​

Mathematics
2 answers:
belka [17]2 years ago
4 0

Answer:

12

Step-by-step explanation:

1s + 14 = 26\\ 1s = 26 - 14 \\ 1s = 12 \\  \\ s =  \frac{12}{1}  \\  \\ s = 12

Thus, The Value Of S is 12

Oduvanchick [21]2 years ago
3 0

Answer:

s = 12

Step-by-step explanation:

1s + 14 = 26 \\ 1s = 26 - 14 \\ 1s = 12 \\  \frac{1s}{1}  =  \frac{12}{1}  \\ s = 12

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Square root3(square root3+2square root12) simplify it.Answer should be square root 3.
julsineya [31]

Answer:

sqrt3[sqrt3+2sqrt12]=sqrt3[sqrt3+4sqrt3] = sqrt3[5sqrt3= 3x5 =15

5 0
2 years ago
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5) An auto dealer offers a compact car, a midsize, a sport utility vehicle, and a light truck, each either in standard, custom,
8090 [49]
You just multiple how many types of vehicles and the property of the vehicle (standard, custom etc.) to get 12 ways
3 0
3 years ago
-3x + 6 = 18 I want the answer
zhenek [66]
-3x + 6 = 18...subtract 6 from both sides
-3x = 18 - 6
-3x = 12...divide both sides by -3
x = -12/3 reduces to -4 <===
7 0
3 years ago
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Please helppppp please asap
Ksivusya [100]

Answer:

126.8

Step-by-step explanation:

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6 0
2 years ago
Suppose you take a simple random sample of size n=175 from the population of Reese's Pieces, still assuming that 45% of this pop
Gnesinka [82]

Answer:

The  probability is  P(0.35

Step-by-step explanation:

From the question we are told that

  The sample size is  n =  175

   The population proportion is  p =  0.45

   

Generally the mean of the sampling distribution is  \mu_{x} =  0.45

 Generally the standard deviation is mathematically represented as  

        \sigma_{x} =  \sqrt{\frac{p (1-p)}{n} }

=>      \sigma_{x} =  \sqrt{\frac{0.45 (1-0.45)}{175} }

=>      \sigma_{x} = 0.0376

Generally the probability of  that the sample proportion of orange candies will be between 0.35 and  0.55 is  

      P(0.35 <  X < 0.55) =  P( \frac{0.35 - 0.45}{0.0376} <  \frac{X -\mu_{x}}{\sigma_{x}}  <  \frac{0.55 - 0.45}{0.0376} )

=>   P(0.35

Generally \frac{X - \mu_{x}}{\sigma_{x}}  =  Z  (The \  standardized \  value \  of  X)

So

    P(0.35

=>  P(0.35

From the z-table  

    P(  Z< 2.6595 ) = 0.99609

and

    P(  Z< - 2.6595 ) = 0.0039128

So

   P(0.35

=> P(0.35

3 0
2 years ago
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