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Elis [28]
3 years ago
12

Marta wants to purchase charms for her necklace. Each charm cost $1.59. She wants to spend no more than $20 for the charms. Whic

h inequality represents this situation? How many charms can Marta purchase
Mathematics
1 answer:
Svetllana [295]3 years ago
5 0

Which inequality represents this situation ?

1.59×n < 20

How many charms can Marta purchase ?

20 : 1.59 = 12 (+$0.92)

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Irina-Kira [14]

Answer:

This term would not change at all when combining like terms.

Step-by-step explanation:

Because the first term has a variable and the second does not, they can not be combined. Therefore, there is not change to this assignment

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The Acme Company manufactures widgets. The distribution of widget weights is bell-shaped. The widget weights have a mean of 46 o
meriva

Answer:

(a) 68% of the widget weights lie between <u>43 ounces</u> and <u>49 ounces</u>.

(b) The percentage of the widget weights lie between 43 and 87 ounces is 15.87%.

(c) The percentage of the widget weights lie below 76 is 100%.

Step-by-step explanation:

Let <em>X</em> = weight of widgets manufactured by Acme Company.

The distribution of the random variable <em>X</em> is, N (<em>μ </em>= 46, <em>σ</em>²<em> </em>=<em> </em>3²).

According to the Empirical Rule in a normal distribution with mean <em>µ</em> and standard deviation <em>σ</em>, nearly all the data will fall within 3 standard deviations of the mean. The empirical rule can be broken into three parts:

  • 68% data falls within 1 standard deviation of the mean.                       That is P (µ - σ ≤ X ≤ µ + σ) = 0.68.
  • 95% data falls within 2 standard deviations of the mean.                   That is P (µ - 2σ ≤ X ≤ µ + 2σ) = 0.95.
  • 99.7% data falls within 3 standard deviations of the mean.                   That is P (µ - 3σ ≤ X ≤ µ + 3σ) = 0.997.

(a)

According to the Empirical rule, 68% data falls within 1 standard deviation of the mean.

P (µ - σ ≤ X ≤ µ + σ) = 0.68.

Compute the upper and lower values as follows:

<em>µ</em> - <em>σ</em> = 46 - 3 = 43 ounces

<em>µ</em> + <em>σ</em> = 46 + 3 = 49 ounces

Thus, 68% of the widget weights lie between <u>43 ounces</u> and <u>49 ounces</u>.

(b)

Compute the probability of the widget weights lie between 43 and 87 ounces as follows:

P(43

                          =P(-1

*Use a <em>z</em>-table.

The percentage is, 0.1587 × 100 = 15.87%.

Thus, the percentage of the widget weights lie between 43 and 87 ounces is 15.87%.

(c)

Compute the probability of the widget weights lie below 76 as follows:

P(X

                  =P(Z

*Use a <em>z</em>-table.

The percentage is, 1 × 100 = 100%.

Thus, the percentage of the widget weights lie below 76 is 100%.

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