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Gnesinka [82]
3 years ago
14

The value of your father’s car when bought was $30,000. If it loses 10% of its value every year, how long until the vehicle is o

nly worth $20,000?
Mathematics
1 answer:
Anvisha [2.4K]3 years ago
6 0

Answer:

6.7

Step-by-step explanation:

10% of 30000

10/100 x 30000

0.10 x 30000

=3000

In order to find how long you have to divide 20k with 3k

20000/3000 = 6.66666667

Round it up and you get 6.7

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Hundreds: 7
tenths: 0
thousandths: 1

5 0
3 years ago
HELP PLEASE PLEASE PLEASE
CaHeK987 [17]

Answer:

If you beg for help like that you won't get any.

Step-by-step explanation:

6 0
2 years ago
Which expression is equivalent to x + 0.2x<br><br>1.2x<br>0.2x squared <br>0.2x <br>1.02x​
Aleks04 [339]
The answer to this expression would be 1.2x
4 0
2 years ago
A manufacturer knows that their items have a normally distributed length, with a mean of 15.4 inches, and standard deviation of
Masteriza [31]

Answer:

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

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.

Mean of 15.4 inches, and standard deviation of 3.5 inches.

This means that \mu = 15.4, \sigma = 3.5

16 items are chosen at random

This means that n = 16, s = \frac{3.5}{\sqrt{16}} = 0.875

What is the probability that their mean length is less than 16.8 inches?

This is the p-value of Z when X = 16.8. So

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

By the Central Limit Theorem

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

Z = \frac{16.8 - 15.4}{0.875}

Z = 1.6

Z = 1.6 has a p-value of 0.9452.

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

5 0
2 years ago
Find the domain and range
almond37 [142]

Answer:

See answer above.

Step-by-step explanation:

These are the ordered pairs on the graph: (-2, 5), (2, 3), (-3, -2), (0, -5), (3, -6)

The domain is the first point in teach ordered pair and the range is the second number in the ordered pair.

So the domain is {-2, 2 , -3, 0, 3}

Range is {5, 3, -2, -5, -6}

6 0
2 years ago
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