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Mama L [17]
2 years ago
7

- A butcher combined 100 lb of hamburger that cost $1.75 per pound with 40 lb of hamburger

Mathematics
2 answers:
slamgirl [31]2 years ago
8 0

Answer:

$315

Step-by-step explanation:

1.75 x 100 = $175

3.50 x 40 =$140

175 + 140 = $315

serious [3.7K]2 years ago
6 0

100 * 1.75 = 175

40 * 3.50 = 140

140lbs of hamburger for $315

The whole mixture sells for $315

315/140 = 2.25

1 pound of the mixture costs $2.25.

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Solve each problem. Explain or show your reasoning.<br> What is 25% of 160 ?
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0.25 x 160 = 40. So 40 is 25% of 160

Step-by-step explanation:

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P(x) = 2x² + 1<br> What is the inverse for p(x)?
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Answer:

P^{-1} (x)=\sqrt{\frac{x-1}{2} }

Step-by-step explanation:

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Which question is a statistical question
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Cause you can actually get multiple different answeres which you can make a statistical question on

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2 years ago
: Use The TI Calculator To Answer The Question. Find The Probability That A Z-score Will Be Between 0.7 And 1.4. A) 0.242 O B) 0
ZanzabumX [31]

Answer:

P(0.7

And we can find this probability with the following difference:

P(0.7

We can use the following commands on the ti 84

2nd>VARS>DISTR

And then we look for normalcdf and we input this:

normalcdf(0.7,1.4,0,1)

The other possible code would be:

normalcdf(-1000,1,4,0,1)-normalcdf(-1000,0.7,0,1)

And we got:

P(0.7

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

For this case we want to find this probability:

P(0.7

And we can find this probability with the following difference:

P(0.7

We can use the following commands on the ti 84

2nd>VARS>DISTR

And then we look for normalcdf and we input this:

normalcdf(0.7,1.4,0,1)

The other possible code would be:

normalcdf(-1000,1,4,0,1)-normalcdf(-1000,0.7,0,1)

And we got:

P(0.7

3 0
3 years ago
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