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Katarina [22]
2 years ago
10

Use the function p(x)=4x-3 what is p(3)

Mathematics
2 answers:
alexandr1967 [171]2 years ago
7 0

Answer:

9!

Step-by-step explanation:

Use the given functions to set up and simplify  p ( 3 ) .

-barbara  

Anestetic [448]2 years ago
6 0

Answer:

9

Step-by-step explanation:

p(x)= 4X-3

P(3)= 4×3-3=9

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Product A is 82% change rate, while 
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product B is 42% change rate

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3 0
3 years ago
Each time Kristine gets paid, she spends $20 and saves the rest. If the amount Kristine earns is represented by x and the amount
bearhunter [10]

Answer:

y=x-20

Step-by-step explanation:

Each time Kristine gets paid, she spends $20 and saves the rest.

Let the amount Kristine earns is represented by x.

Let the amount she saves is represented by y.

The equation forms:

y=x-20

So, the graph demonstrating this will be the answer.

3 0
3 years ago
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What is the probability of drawing an ace or a jack out of a standard card deck?
Tom [10]
There are 4 of each card

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4+4=8

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7 0
3 years ago
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Trent saved up $500 for summer vacation. If he spends $25 a week for eight weeks, how much money does he have left? Explain? (Ca
Alex17521 [72]

Answer:300

Step-by-step explanation:

25*8 =200

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6 0
3 years ago
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The mean of a population is 74 and the standard deviation is 16. The shape of the population is unknown. Determine the probabili
bulgar [2K]

Answer:

a

 P(X  >  75)=  0.35402

b

P(72 <  X  <  75 ) = 0.2529

c

P( X  <  74.7)  = 0.74041

Step-by-step explanation:

From the question we are told that

  The population mean is  \mu =  74

  The population standard deviation is  \sigma  =  16

 Considering question a  

    The sample size is  n  =  36  

Generally the standard error of mean is mathematically represented as

     \sigma_{x} =  \frac{\sigma  }{\sqrt{n} }

=>  \sigma_{x} =  \frac{16}{\sqrt{36} }

=>  \sigma_{x} = 2.67

Generally the probability that a  random sample of size 36 yielding a sample mean of 75 or more is mathematically represented as

     P(X  >  75) =  P( \frac{X -  \mu  }{ \sigma_{x}} >  \frac{75 -  74}{ 2.67 }  )

\frac{X -\mu}{\sigma }  =  Z (The  \ standardized \  value\  of  \ X )

   P(X  >  75) =  P(Z >  0.3745   )

From the z table  the area under the normal curve representing 0.3745 to the right is  

     P(Z >  0.3745   ) =  0.35402

=>   P(X  >  75)=  0.35402

 Considering question b  

    The sample size is  n  =  104

Generally the standard error of mean is mathematically represented as

     \sigma_{x} =  \frac{\sigma  }{\sqrt{n} }

=>  \sigma_{x} =  \frac{16}{\sqrt{104} }

=>  \sigma_{x} = 1.5689

Generally the probability that a random sample of size 104 yielding a sample mean  between 72 and 75 is mathematically represented as

      P(72 <  X  <  75 ) =  P(\frac{72 - 74 }{1.5689}  <  \frac{X -  \mu }{\sigma_{x}}  < \frac{75 - 74 }{1.5689}   )

=>   P(72 <  X  <  75 ) =  P(-1.275 < Z < 0.375   )

=>   P(72 <  X  <  75 ) =  P(Z < 0.375   ) -  P(Z <  -1.275)

From the z table  the area under the normal curve representing -1.275 to to the left is

   P(Z <  -1.275) =0.10115

=> P(72 <  X  <  75 ) = 0.35402  -  0.10115

=> P(72 <  X  <  75 ) = 0.2529

Considering question c

    The sample size is  n  =  217

Generally the standard error of mean is mathematically represented as

     \sigma_{x} =  \frac{\sigma  }{\sqrt{n} }

=>  \sigma_{x} =  \frac{16}{\sqrt{217} }

=>  \sigma_{x} = 1.086

Generally the probability that a  random sample of size 217 yielding a sample mean of less than 74.7 is mathematically represented as

       P( X  <  74.7) =  P(\frac{X -  \mu }{\sigma_x}  < \frac{ 74.7 -  74 }{ 1.086 })

=>   P( X  <  74.7) =  P(Z < 0.6446 )

From the z table  the area under the normal curve representing 0.6446  to to the left is

     P(Z < 0.6446 )  =  0.74041

=>  P( X  <  74.7)  = 0.74041

8 0
3 years ago
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