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Softa [21]
3 years ago
14

Best estimate of 48% of 159

Mathematics
1 answer:
olga55 [171]3 years ago
8 0

Answer:

76.32

Step-by-step explanation:

Move the decimal point two times to the left 48. --> .48

Multiply .48 by 159

= 76.32

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yulyashka [42]

Answer:

34° is the closest to the record high in degree Fahrenheit ⇒ C

Step-by-step explanation:

∵ The formula F = \frac{9}{5} C + 32 is used to convert the temperature from

    degrees Celsius (C) to degree Fahrenheit (F)

∵ The high temperature in Chicago is 1° Celsius

→ Substitute C in the formula above by 1

∴ F = \frac{9}{5} (1) + 32

∴ F =  \frac{9}{5}  + 32

∴ F = 33.8°

→ Round it to the nearest degree Fahrenheit

∴ F ≅ 34°

∴ 34° is the closest to the record high in degree Fahrenheit

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2 years ago
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Answer:

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Step-by-step explanation:

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2 years ago
Can you help me with number 5?
Verizon [17]

We can divide that up into two rectangles, say the bottom one 8 feet wide and 2 feet high.  That leaves 5.5 by 6-2=4 feet for the other.

Cost = price × area = 2.25(8×2 + 5.5×4) = $85.50

Answer: $85.50

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Step-by-step explanation:

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2 years ago
A given population proportion is .25. What is the probability of getting each of the following sample proportions
anyanavicka [17]

This question is incomplete, the complete question is;

A given population proportion is .25. What is the probability of getting each of the following sample proportions

a) n = 110 and = p^ ≤ 0.21, prob = ?

b) n = 33 and p^ > 0.24, prob = ?

Round all z values to 2 decimal places. Round all intermediate calculation and answers to 4 decimal places.)

Answer:

a) the probability of getting the sample proportion is 0.1660

b) the probability of getting the sample proportion is 0.5517

Step-by-step explanation:

Given the data in the questions

a)

population proportion = 0.25

q = 1 - p = 1 - 0.25 = 0.75

sample size n = 110

mean = μ = 0.25

S.D = √( p( 1 - p) / n ) = √(0.25( 1 - 0.25) / 110 ) √( 0.1875 / 110 ) = 0.0413

Now, P( p^ ≤ 0.21 )

= P[ (( p^ - μ ) /S.D) < (( 0.21 - μ ) / S.D)

= P[ Z < ( 0.21 - 0.25 ) / 0.0413)

= P[ Z < -0.04 / 0.0413]

= P[ Z < -0.97 ]

from z-score table

P( X ≤ 0.21 ) = 0.1660

Therefore, the probability of getting the sample proportion is 0.1660

b)

population proportion = 0.25

q = 1 - p = 1 - 0.25 = 0.75

sample size n = 33

mean = μ = 0.25

S.D = √( p( 1 - p) / n ) = √(0.25( 1 - 0.25) / 33 ) = √( 0.1875 / 33 ) = 0.0754

Now, P( p^ > 0.24 )  

= P[ (( p^ - μ ) /S.D) > (( 0.24 - μ ) / S.D)

= P[ Z > ( 0.24 - 0.25 ) / 0.0754 )

= P[ Z > -0.01 / 0.0754  ]

= P[ Z > -0.13 ]

= 1 - P[ Z < -0.13 ]

from z-score table

{P[ Z < -0.13 ] = 0.4483}

1 - 0.4483

P( p^ > 0.24 )  = 0.5517

Therefore, the probability of getting the sample proportion is 0.5517

6 0
2 years ago
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