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nordsb [41]
3 years ago
9

During a scuba dive, Lainey descended to a point 29 feet below the ocean surface. She continued her descent at a rate of 29 feet

per minute. Enter an inequality you could solve to find the number of minutes she can continue to descend if she does not want to reach a point more than 81 feet below the ocean surface. Use t to represent the variable for the minutes Lainey can continue to descend.
Mathematics
1 answer:
Alex73 [517]3 years ago
6 0

Answer:

Her initial position was:

-29ft

Where we use the minus sign because this is below the ocean's surface.

Now we also know that she keeps descending at a rate of -29ft per minute, then if she keeps descending for t minutes, her position will be:

P(x) = -29ft - 29ft/min*t

Now, we also know that she does not want to descend more than 81ft below the ocean's surface, then we have the inequality:

P(x) ≥ -81ft

-29ft - 29ft/min*t ≥ -81ft

Now let's isolate t in one side:

- 29ft/min*t ≥ -81ft + 29ft = -52 ft

- 29ft/min*t ≥-52 ft

                t ≤ -52ft/(- 29ft/min) = 1.79 min

Then the maximum amount of time that she can keep descending is 1.79 minutes.

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hichkok12 [17]

Answer:

0.007 = 0.7% probability that the proportion of Rolls Royce owners in a sample of 595 Americans would differ from the population proportion by more than 3%

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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

A statistician calculates that 8% of Americans own a Rolls Royce.

This means that p = 0.08

Sample of 595:

This means that n = 595

Mean and standard deviation:

\mu = p = 0.08

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.08*0.92}{595}} = 0.0111

What is the probability that the proportion of Rolls Royce owners in a sample of 595 Americans would differ from the population proportion by more than 3%?

Proportion above 8% + 3% = 11% or below 8% - 3% = 5%. Since the normal distribution is symmetric, these probabilities are equal, and so we find one of them and multiply by 2.

Probability the proportion is less than 5%:

P-value of Z when X = 0.05. So

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

By the Central Limit Theorem

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

Z = \frac{0.05 - 0.08}{0.0111}

Z = -2.7

Z = -2.7 has a p-value of 0.0035

2*0.0035 = 0.0070

0.007 = 0.7% probability that the proportion of Rolls Royce owners in a sample of 595 Americans would differ from the population proportion by more than 3%

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