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Degger [83]
3 years ago
7

Which expression is equal to 632?

Mathematics
1 answer:
kkurt [141]3 years ago
3 0

Answer:

3. 2^{3} (3*5^{2}  + 2^{2} )

Step-by-step explanation:

I think your question missed key information, allow me to add in and hope it will fit the orginal one. Please have a look at the attached photo

My answer;

We use oder of operation to solve this question

We have BEDMAS, which means:

  • B - Brackets
  • E - Exponents
  • D - Division
  • M - Multiplication
  • A - Addition
  • S - Subtraction

In 4 answer, only answer is correct:

2^{3} (3*5^{2}  + 2^{2} )

= 2^{3} (3*25 +4)

= 2^{3} (79 + 4)

= 2^{3}*83

= 8*83

= 664

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Find the space inside a rectangle with a width of 8 and a length of 15. ​
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120

Step-by-step explanation:

A=LxH

So 15x8=120

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2bc
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2 years ago
How do you solve an inequality that has a fraction (with a variable as the nemurator/demoninator
vichka [17]

Answer:

Solving with an equality is just simply the same as solving any algebra equations. If you were given a fraction, then just multiply both sides.

Example:

4 + \frac{x}{2} > 14

Subtract 4 on both sides:

4 - 4 + \frac{x}{2} > 14 - 4

\frac{x}{2} > 10

Now <em>multiply both sides by 2</em>:

\frac{x}{2} × 2 > 10 × 2

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3 0
3 years ago
According to an NRF survey conducted by BIGresearch, the average family spends about $237 on electronics (computers, cell phones
Usimov [2.4K]

Answer:

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is 0.0537.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is 0.0023.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is 0.1101.

Step-by-step explanation:

We are given that according to an NRF survey conducted by BIG research, the average family spends about $237 on electronics in back-to-college spending per student.

Suppose back-to-college family spending on electronics is normally distributed with a standard deviation of $54.

Let X = <u><em>back-to-college family spending on electronics</em></u>

SO, X ~ Normal(\mu=237,\sigma^{2} =54^{2})

The z score probability distribution for normal distribution is given by;

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

where, \mu = population mean family spending = $237

           \sigma = standard deviation = $54

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is = P(X < $150)

        P(X < $150) = P( \frac{X-\mu}{\sigma} < \frac{150-237}{54} ) = P(Z < -1.61) = 1 - P(Z \leq 1.61)

                                                             = 1 - 0.9463 = <u>0.0537</u>

The above probability is calculated by looking at the value of x = 1.61 in the z table which has an area of 0.9463.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is = P(X > $390)

        P(X > $390) = P( \frac{X-\mu}{\sigma} > \frac{390-237}{54} ) = P(Z > 2.83) = 1 - P(Z \leq 2.83)

                                                             = 1 - 0.9977 = <u>0.0023</u>

The above probability is calculated by looking at the value of x = 2.83 in the z table which has an area of 0.9977.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is given by = P($120 < X < $175)

     P($120 < X < $175) = P(X < $175) - P(X \leq $120)

     P(X < $175) = P( \frac{X-\mu}{\sigma} < \frac{175-237}{54} ) = P(Z < -1.15) = 1 - P(Z \leq 1.15)

                                                         = 1 - 0.8749 = 0.1251

     P(X < $120) = P( \frac{X-\mu}{\sigma} < \frac{120-237}{54} ) = P(Z < -2.17) = 1 - P(Z \leq 2.17)

                                                         = 1 - 0.9850 = 0.015

The above probability is calculated by looking at the value of x = 1.15 and x = 2.17 in the z table which has an area of 0.8749 and 0.9850 respectively.

Therefore, P($120 < X < $175) = 0.1251 - 0.015 = <u>0.1101</u>

5 0
3 years ago
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