(6.31x10⁵)+(2.6x10⁴)

Mathematics

1 answer:

WINSTONCH [101]4 years ago

7 0

Answer:

6.57 * 10^5.

Step-by-step explanation:

(6.31x10⁵)+(2.6x10⁴)

First convert to standard form:

= 631000 + 26000

= 657000

= 6.57 * 10^5.

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A cube has a volume of 64. What is the length of one side of the cube?

bearhunter [10]

Answer:

Step-by-step explanation:

The volume of a cube can be represented as s^3 = v, where s = side and v = volume. In this case, we're given the volume as 64, so s^3 = 64. To solve this problem, we first have to know what a cube root is.

What's a cube root?

The cube root of a number is the number you multiply by itself 3 times to get another number.
One common cube is 27, and the cube root of it is 3 because 3 x 3 x 3 = 27.

Given the information above, let's go in order with the list of cube roots to see which one has a cube of 64.

1: 1 x 1 x 1 = 1.
2: 2 x 2 x 2 = 8.
3: 3 x 3 x 3 = 27.
4: 4 x 4 x 4 = 64. (This is the cube root!)

We found the cube root of 64, or the side of the cube with a volume of 64. The side of the cube, therefore, is 4.

Have a lovely rest of your day/night, and good luck with your assignments! ♡

3 0

3 years ago

Solve the problem. Use the Central Limit Theorem.The annual precipitation amounts in a certain mountain range are normally distr

bazaltina [42]

Answer:

0.8944 = 89.44% probability that the mean annual precipitation during 25 randomly picked years will be less than 112 inches.

Step-by-step explanation:

To solve this question, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .