Ask question

Ask question

All categories

2 years ago

15

Parker signed up for a streaming music service that costs $6 per month. The service allows Parker to listen to unlimited music,

but if he wants to download songs for offline listening, the service charges $0.50 per song. How much total money would Parker have to pay in a month in which he downloaded 50 songs? How much would he have to pay if he downloaded ss songs?

1 answer:

Sloan [31]2 years ago

3 0

Answer:

Parker will have to pay $31 in a month in which he downloaded 50 songs.

Total amount Parker will pay for s songs = 6 + 0.50s

Step-by-step explanation:

Cost per month = $6

Cost of Offline download = $0.50 per song

A. How much total money would

Parker have to pay in a month in which he downloaded 50 songs?

Total amount Parker will pay = $6 + $0.50(50)

= 6 + 25

= $31

Parker will have to pay $31 in a month in which he downloaded 50 songs.

B. How much would

he have to pay if he downloaded s songs?

Total amount Parker will pay for s songs = $6 + $0.50 * s

= $6 + $0.50s

Total amount Parker will pay for s songs = 6 + 0.50s

You might be interested in

The time for a visitor to read health instructions on a Web site is approximately normally distributed with a mean of 10 minutes

klio [65]

Answer:

a) The mean is 10 and the variance is 0.0625.

b) 0.6826 = 68.26% probability that the mean time of the visitors is within 15 seconds of 10 minutes.

c) 10.58 minutes.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value 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. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Normally distributed with a mean of 10 minutes and a standard deviation of 2 minutes.

This means that $\mu = 10, \sigma = 2$

Suppose 64 visitors independently view the site.

This means that $n = 64, = \frac{2}{\sqrt{64}} = 0.25$

a. The expected value and the variance of the mean time of the visitors.

Using the Central Limit Theorem, mean of 10 and variance of (0.25)^2 = 0.0625.

b. The probability that the mean time of the visitors is within 15 seconds of 10 minutes.

15 seconds = 15/60 = 0.25 minutes, so between 9.75 and 10.25 seconds, which is the p-value of Z when X = 10.25 subtracted by the p-value of Z when X = 9.75.

X = 10.25

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{10.25 - 10}{0.25}$

$Z = 1$

$Z = 1$ has a p-value of 0.8413.

X = 9.75

$Z = \frac{X - \mu}{s}$

$Z = \frac{9.75 - 10}{0.25}$

$Z = -1$

$Z = -1$ has a p-value of 0.1587.

0.8413 - 0.1587 = 0.6826.

0.6826 = 68.26% probability that the mean time of the visitors is within 15 seconds of 10 minutes.

c. The value exceeded by the mean time of the visitors with probability 0.01.

The 100 - 1 = 99th percentile, which is X when Z has a p-value of 0.99, so X when Z = 2.327.

$Z = \frac{X - \mu}{s}$

$2.327 = \frac{X - 10}{0.25}$

$X - 10 = 2.327*0.25$

$X = 10.58$

So 10.58 minutes.

6 0

3 years ago

Can someone please help me with this!!!

user100 [1]

It is an arithmetic because it is adding 2 to each number.

7 0

3 years ago

The Wall Street Journal reports that 33% of taxpayers with adjusted gross incomes between $30,000 and $60,000 itemized deduction

Len [333]

Answer:

(a) <em> </em><em>n</em> : 20 50 100 500

P (-200 < <em>X</em> - <em>μ </em>< 200) : 0.2886 0.4444 0.5954 0.9376

(b) The correct option is (b).

Step-by-step explanation:

Let the random variable <em>X</em> represent the amount of deductions for taxpayers with adjusted gross incomes between $30,000 and $60,000 itemized deductions on their federal income tax return.

The mean amount of deductions is, <em>μ</em> = $16,642 and standard deviation is, <em>σ</em> = $2,400.

Assuming that the random variable <em>X </em>follows a normal distribution.

(a)

Compute the probability that a sample of taxpayers from this income group who have itemized deductions will show a sample mean within $200 of the population mean as follows:

For a sample size of <em>n</em> = 20

$P(\mu-200$

$=P(-0.37$

For a sample size of <em>n</em> = 50

$P(\mu-200$

$=P(-0.59$

For a sample size of <em>n</em> = 100

$P(\mu-200$

$=P(-0.83$

For a sample size of <em>n</em> = 500

$P(\mu-200$

$=P(-1.86$

<em> n</em> : 20 50 100 500

P (-200 < <em>X</em> - <em>μ </em>< 200) : 0.2886 0.4444 0.5954 0.9376

(b)

The law of large numbers, in probability concept, states that as we increase the sample size, the mean of the sample ( $\bar x$ ) approaches the whole population mean ( $\mu_{x}$ ).

Consider the probabilities computed in part (a).

As the sample size increases from 20 to 500 the probability that the sample mean is within $200 of the population mean gets closer to 1.

So, a larger sample increases the probability that the sample mean will be within a specified distance of the population mean.

Thus, the correct option is (b).

8 0

3 years ago

Based on the Nielsen ratings, the local CBS affiliate claims its 10 p.m. newscast reaches 41% of the viewing audience in the are

damaskus [11]

Answer:

H0:p=0.41

Step-by-step explanation:

The null hypothesis always contain equality i.e. (=) sign. The null hypothesis contains the statement regarding population parameter. Here, the claim about population proportion is mentioned in the statement that 10 p.m. newscast of local CBS reaches 41% of viewers. So, the null hypothesis would be

Null hypothesis:H0: p=0.41.

4 0

2 years ago

there are 28 tables in the cafeteria.each table has 12 students sitting at it.fourth graders sit at 13 of the yables.fifth grade

Darya [45]

Hope this helps!

28 - 13 = 15
15 x 12 = 180 Fifth graders

6 0

3 years ago