2) Prove that these two lines are parallel:

Two cubes have their surface areas in the ratio 1:4 , what is the ratio of their volumes ?

yKpoI14uk [10]

Answer:

1 : 8

Step-by-step explanation:

For similar figures with ratio of sides = a : b

Then ratio of areas = a² : b² and

ratio of volumes = a³ : b³

Given ratio of areas = 1 : 4

linear ratio = $\sqrt{1}$ : $\sqrt{4}$ = 1 : 2

ratio of volumes = 1³ : 2³ = 1 : 8

8 0

3 years ago

Bagaimana cara membuktikan bahwa persamaan garis tegak lurus itu benar

Tems11 [23]

Ketika dua garis tegak lurus, kemiringan satu adalah timbal balik negatif dari yang lain.Jika kemiringan satu baris adalah m, kemiringan yang lain adalahCoba ini Drag poin C atau D. Catatan lereng ketika garis tegak lurus satu sama lain.
Ketika dua garis tegak lurus satu sama lain (di sudut kanan atau 90 °), lereng mereka memiliki hubungan khusus satu sama lain. Jika kemiringan satu baris adalah m maka kemiringan garis lainnya adalah timbal balik negatif m.

7 0

3 years ago

CNNBC recently reported that the mean annual cost of auto insurance is 965 dollars. Assume the standard deviation is 113 dollars

velikii [3]

Answer:

P(939.6 < X < 972.5) = 0.6469

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 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 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 $s = \frac{\sigma}{\sqrt{n}}$ .