You buy a new computer for $1,500. The value of the computer decreases by 6%

Mathematics

2 answers:

bija089 [108]3 years ago

6 0

Answer:

Hey there!

Each year, the computer is (100-6), or 94% of it's original value.

Thus, we have:

Original: 1500

First year: 1500(0.94)

Second year: 1500(0.94)(0.94)

Third year: 1500(0.94)(0.94)(0.94)

Fourth year: 1500(0.94)(0.94)(0.94)(0.94)

Fourth year: 1171 dollars.

Hope this helps :)

Naya [18.7K]3 years ago

5 0

Answer:

$1171.05

Step-by-step explanation:

1500 × (1-(6 / 100))⁴

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A woman is randomly selected from the 18–24 age group. For women of this group, systolic blood pressures (in mm Hg) are normally

Naddik [55]

Answer:

$X \sim N(114.8,13.1)$

Where $\mu=114.8$ and $\sigma=13.1$

We are interested on this probability

$P(X>140)$

And the best way to solve this problem is using the normal standard distribution and the z score given by:

$z=\frac{x-\mu}{\sigma}$

If we apply this formula to our probability we got this:

And we can find this probability using the complement rule:

$P(z>1.924)=1-P(z$

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

Solution to the problem

Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:

$X \sim N(114.8,13.1)$

Where $\mu=114.8$ and $\sigma=13.1$

We are interested on this probability

$P(X>140)$

And the best way to solve this problem is using the normal standard distribution and the z score given by:

$z=\frac{x-\mu}{\sigma}$

If we apply this formula to our probability we got this: $P(X>140)=P(\frac{X-\mu}{\sigma}>\frac{140-\mu}{\sigma})=P(Z>\frac{140- 1114.8}{2.6})=P(z>1.924)$ And we can find this probability using the complement rule: