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Sergeeva-Olga [200]
3 years ago
6

John and Alan have a collection of x baseball cards. John has x/4 cards. What fraction of the cards does Alan have?

Mathematics
2 answers:
maw [93]3 years ago
8 0

Answer: B. \frac{3x}{4}

Step-by-step explanation:

Given: The total number of cards John and Alan has = x

The number of cards John has = \frac{x}{4}

Then to find the number of cards Alan has, we need to subtract the number of cards John has from the total number of cards.

Then, the number of cards John has =x-\frac{x}{4}

⇒ The number of cards John has =\frac{4x-x}{4}

⇒ The number of cards John has =\frac{3x}{4}

Furkat [3]3 years ago
3 0
The fraction of cards that Alan has is 3x/4. The correct answer is B. 

x-x/4
4x-x/4
3x/4
he has 3x/4 cards
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The weight of National Football League (NFL) players has increased steadily, gaining up to 1.5 lb. per year since 1942. Accordin
GuDViN [60]

Answer:

The probability that the sample mean weight will be more than 262 lb is 0.0047.

Step-by-step explanation:

The random variable <em>X</em> can be defined as the weight of National Football League (NFL) players now.

The mean weight is, <em>μ</em> = 252.8 lb.

The standard deviation of the weights is, <em>σ</em> = 25 lb.

A random sample of <em>n</em> = 50 NFL players are selected.

According to the Central Limit Theorem if we have an unknown population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.

Then, the mean of the sample means is given by,

\mu_{\bar x}=\mu

And the standard deviation of the sample means is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

The sample of players selected is quite large, i.e. <em>n</em> = 50 > 30, so the central limit theorem can be used to approximate the distribution of sample means.

\bar X\sim N(\mu_{\bar x}=252.8,\ \sigma_{\bar x}=3.536)

Compute the probability that the sample mean weight will be more than 262 lb as follows:

P(\bar X>262)=P(\frac{\bar X-\mu_{\bar x}}{\sigma_{\bar x}}>\frac{262-252.8}{3.536})\\\\=P(Z>2.60)\\\\=1-P(Z

*Use a <em>z</em>-table for the probability.

Thus, the probability that the sample mean weight will be more than 262 lb is 0.0047.

6 0
3 years ago
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A line perpendicular to another has a slope that is the negative reciprocal of the slope of the other line. The negative reciprocal of the original line is –2, and is thus the slope of its perpendicular line
7 0
2 years ago
ILS
Drupady [299]

Answer:

120.7

Step-by-step explanation:

14.2 • 8.5

The • sign means multiplication

14.2 x 8.5

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