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3 years ago

Simplify the problem thank you

Mathematics

2 answers:

never [62]3 years ago

8 0

Answer:

-5

Step-by-step explanation:

(-5)(-5)(-5)=-125

NikAS [45]3 years ago

5 0

Given the expression:

$\displaystyle \large{ \sqrt[3]{ - 125} }$

Definition:

$\displaystyle \large{ y = \begin{cases} \pm \sqrt[n]{x} \longrightarrow n = (2,4,6,8,...) \: \: (x \geqslant 0) \\ \sqrt[n]{x}\longrightarrow n = (1,3,5,7,...) \: \: (x \in \R) \end{cases}}$

First, factor the -125. -125 comes from (-5)×(-5)×(-5) or (-5)^3.

$\displaystyle \large{ \sqrt[3]{ ( - 5) \times ( - 5) \times ( - 5)} }$

Because if (-5)^2 = 25 then 25×(-5) again will be -125.

Since this is the cube root, we have to pull out 3 terms in one. There are 3 fives that we can take off and therefore,

$\displaystyle \large \boxed{ - 5}$

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Jules is measuring a patient’s height at 4 feet What is this height in inches? Answer

kondor19780726 [428]

Answer:

48 inches

Step-by-step explanation:

There are 12 inches in 1 foot. So multiply by 12 to convert from feet to inches.

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3 0

2 years ago

An article written for a magazine claims that 78% of the magazine's subscribers report eating healthily the previous day. Suppos

Schach [20]

Answer:

89.44% probability that less than 80% of the sample would report eating healthily the previous day

Step-by-step explanation:

We use the binomial approximation to the normal to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

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.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .