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IRISSAK [1]
2 years ago
11

8(p-6) > 4(p-4) How do I solve?

Mathematics
2 answers:
Scrat [10]2 years ago
6 0

Answer:

p > 8

Step-by-step explanation:

8p - 48 > 4p - 16

plus 48 on both sides

8p > 4p + 32

minus 4p on both sides

4p > 32

divide 4 on both sides, 32 ÷ 4 = 8, so,

p>8

kumpel [21]2 years ago
4 0

Answer:

P > 8 ??? I don't know if this is right and if its not then sorry lol

Step-by-step explanation:

Multiply 8(p-6) and 4(p-4)

You will get 8p - 48 > 4p - 16

Then add 48 to -16

Then you will get 8p > 4p + 32

Then subtract 4p from 8p

Then you will get 4p > 32

Then divide 4 from 4p and 32

Then you will get p > 8

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Suppose that the population mean for income is $50,000, while the population standard deviation is 25,000. If we select a random
Fudgin [204]

Answer:

Probability that the sample will have a mean that is greater than $52,000 is 0.0057.

Step-by-step explanation:

We are given that the population mean for income is $50,000, while the population standard deviation is 25,000.

We select a random sample of 1,000 people.

<em>Let </em>\bar X<em> = sample mean</em>

The z-score probability distribution for sample mean is given by;

               Z = \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }  ~ N(0,1)

where, \mu = population mean = $50,000

            \sigma = population standard deviation = $25,000

            n = sample of people = 1,000

The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X.

So, probability that the sample will have a mean that is greater than $52,000 is given by = P(\bar X > $52,000)

  P(\bar X > $52,000) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{52,000-50,000}{\frac{25,000}{\sqrt{1,000} } } ) = P(Z > 2.53) = 1 - P(Z \leq 2.53)

                                                                    = 1 - 0.9943 = 0.0057

<em>Now, in the z table the P(Z </em>\leq<em> x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 2.53 in the z table which has an area of 0.9943.</em>

Therefore, probability that the sample will have a mean that is greater than $52,000 is 0.0057.

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