Felicia filled the bathroom sink with water is the amour more than 1 liter about 1 liter or less than 1 liter

1 answer:

6 0

There are a lot of different sinks. Different sizes and different shapes, but what is almost certainly true is that they all have volume bigger than 1 liter. To gain some perspective on the issue try imaging a cube with each edge being 10cm long (approximately 4 inches). Imagine how many of this you could put into a bathroom sink.
So your answer should be more that one liter.

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Select all the factors roots of x^3 +2x^2-16x-32

Ivanshal [37]

Factor by grouping. Group up the terms into pairs, factor each pair, then factor out the overall GCF.

x^3 + 2x^2 - 16x - 32

(x^3 + 2x^2) + (-16x-32) ... pair up terms

x^2(x + 2) + (-16x - 32) ... factor x^2 from the first group

x^2(x + 2) - 16(x + 2) ... factor -16 from the second group

(x^2 - 16)(x + 2) .... factor out (x+2)

(x - 4)(x + 4)(x + 2) .... Use the difference of squares to factor x^2-16

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The original expression completely factors to (x - 4)(x + 4)(x + 2)

The three factors are x - 4 and x + 4 and x + 2

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3 years ago

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The annual precipitation amounts in a certain mountain range are normally distributed with a mean of 104 inches, and a standard

dsp73

Answer:

91.92% probability that the mean annual precipitation during 49 randomly picked years will be less than 106.8 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 normally distributed samples are 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.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$