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gizmo_the_mogwai [7]
3 years ago
7

You walk up to a tank of water that can hold up to 20 gallons. When it is active, a drain empties water from the tank at a const

ant rate. When you first see the tank it contains 15 gallons of water. Three minutes later, that tank contains 10 gallons of water.
At what rate is the amount of water in the tank changing? Use a signed number, and include the unit of measurement in your answer.

How many minutes will it take for the tank to drain completely? Explain or show your reasoning.

How many minutes before you arrived was the water tank completely full? Explain or show your reasoning.
Mathematics
1 answer:
Marizza181 [45]3 years ago
7 0

Answer:

5 gallons per 3 minutes

12 minutes to empty it all

it is active so it is holding 20 gallons

Step-by-step explanation:

self explanatory i think

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Step-by-step explanation:

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Mal is putting money into a savings account. She starts with $350 in the savings account, and each week she adds $30.
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S=350+(30*w)
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350+(30*19)=920
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Jessica had m beads. She used 18 of them to make a necklace for her mom. Then she used the rest to make k bracelets for her frie
Y_Kistochka [10]
The expression to represent this would be (m-18)/k.

We first subtract the 18 beads she used in her mother's bracelet from her beginning number, m.  We then divide our result by k, the number of bracelets she made for her friends.
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4 years ago
A particular variety of watermelon weighs on average 20.4 pounds with a standard deviation of 1.23 pounds. Consider the sample m
love history [14]

Answer:

a) The expected value of the sample mean weight is 20.4 pounds.

b)The standard deviation of the sample mean weight is 0.123.

c) There is a 14.46% probability the sample mean weight will be less than 20.27.

d) This value is c = 20.6153.

Step-by-step explanation:

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation \frac{\sigma}{\sqrt{n}}.

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.

In this problem, we have that:

A particular variety of watermelon weighs on average 20.4 pounds with a standard deviation of 1.23 pounds. This means that \mu = 20.4, \sigma = 1.23

Consider the sample mean weight of 100 watermelons of this variety. This means that n = 100.

a. What is the expected value of the sample mean weight? Give an exact answer.

By the Central Limit Theorem, it is the same as the mean of the population. So the expected value of the sample mean weight is 20.4 pounds.

b. What is the standard deviation of the sample mean weight? Give your answer to four decimal places.

By the Central Limit Theorem, that is:

s = \frac{\sigma}{\sqrt{n}} = \frac{1.23}{\sqrt{100}} = 0.123

The standard deviation of the sample mean weight is 0.123.

c. What is the approximate probability the sample mean weight will be less than 20.27?

This is the pvalue of Z when X = 20.27.

Since we are working with the sample mean, we use s instead of \sigma in the Z score formula

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

Z = \frac{20.27 - 20.4}{0.123}

Z = -1.06

Z = -1.06 has a pvalue of 0.1446.

This means that there is a 14.46% probability the sample mean weight will be less than 20.27.

d. What is the value c such that the approximate probability the sample mean will be less than c is 0.96?

This is the value of X = c that is in the 96th percentile, that is, it's Z score has a pvalue 0.96.

So we use Z = 1.75

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

1.75 = \frac{c - 20.4}{0.123}

c - 20.4 = 0.123*1.75

c = 20.6153

This value is c = 20.6153.

6 0
3 years ago
A random sample of 400 voters in a certain city are asked if they favor an additional 4% gasoline tax to provide badly needed re
Norma-Jean [14]

Answer:

A) α = 0.04136

B) β = 0.00256

Step-by-step explanation:

We are given;

Sample size; n = 400

Proportion; p = 60% = 0.6

Formula for mean is;

μ = np

μ = 400 × 0.6 = 240

Standard deviation is given by;

σ = √npq

Where q = 1 - p = 1 - 0.6 = 0.4

σ = √(400 × 0.6 × 0.4)

σ = √96

σ = 9.8

A) our null hypothesis is at p = 0.6

Probability of making a type I error means we reject the null hypothesis when it is true.

This can be expressed in reference to the question as;

α = P(x < 220) + P(x > 260) all at p = 0.6

Now,

P(x < 220) = z = (x¯ - μ)/σ = (220 - 240)/9.8 = -2.04

Also;

P(x > 260) = z = (260 - 240)/9.8 = 2.04

Now, from z-distribution table probability of a z-score of -2.04 is 0.02068.

Also, probability of z-score of 2.04 is (1 - P(z < 2.04) = 1 - 0.97932 = 0.02068

Thus;

α = 0.02068 + 0.02068

α = 0.04136

B) Type II error occurs when we fail to reject the null hypothesis even though it's false.

In this case our alternative hypothesis is at p = 48% = 0.48

Thus;

μ = np

μ = 400 × 0.48 = 192

Standard deviation is given by;

σ = √npq

Where q = 1 - p = 1 - 0.48 = 0.52

σ = √(400 × 0.48 × 0.52)

σ = √99.84

σ = 9.992

Type II error would be given by;

β = [((x1¯ - μ)/σ) < z > ((x2¯ - μ)/σ)]

β = [((220 - 192)/9.992) < z > ((260 - 192)/9.992)]

β = (2.8 < z > 6.81)

Rearranging this gives us;

β = P(z < 6.81) - P(z < 2.8)

From z-distribution tables, we have;

β = 1 - 0.99744

β = 0.00256

3 0
3 years ago
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