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3 years ago

Please help? I really need it

Mathematics

2 answers:

horsena [70]3 years ago

4 0

Answer:

216 in²

Step-by-step explanation:

a = bh

a = 18 * 12

a = 216

victus00 [196]3 years ago

3 0

216 in2 this is because you are finding the area meaning you multiple your two sides

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How much does the atmosphere weigh over each square meter of surface? express this in tonnes (units of 1000 kg). recall the conv

Anettt [7]

Atmospheric pressure = 101,325 Newtons / m²
Weight per meter square = 101,325 Newtons
Mass per meter square = 101,325 / (9.81 x 1000)
Mass per meter square = 10.3 tonnes per m²

7 0

3 years ago

PLZ HELP ASAP!!!!!!!!!!!!!!!!!

eimsori [14]

B and C because both bases are squares

8 0

3 years ago

I dont know how to do math 10 factors

pav-90 [236]

Answer:

10= 1 , 2 , 5 and 10

Step-by-step explanation:

Those are the factors of 10

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3 years ago

If the areas of the given pairs of shapes are equal, find the value of x.

den301095 [7]

Answer:

$x = 8cm$

Step-by-step explanation:

we are given a square and rectangle.we want to figure out x which is the width of the rectangle. we are also given a condition i.e

the area of the square equal to the area of the rectangle

therefore,

$\displaystyle \rm A _{square } = A _{rect}$

recall the formula of the area of square and rectangle so,

$\displaystyle {s}^{2} = lw$

now assign variables

$s \implies16cm$
$l \implies32cm$
$w \implies x$

thus substitute:

$\displaystyle 32cmx = {16cm}^{2}$

simplify square:

$\displaystyle 32cmx = 256cm^2$

divide both sides by 32:

$\displaystyle \boxed{x = 8cm}$

and we're done!

3 0

2 years ago

Read 2 more answers

Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.0 ounces and a standard deviation of 1.1

svet-max [94.6K]

Answer:

a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

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