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2 years ago

SOMEONE ANSWER HURRY PLEASE

Mathematics

1 answer:

Aleksandr-060686 [28]2 years ago

8 0

Answer:

A, B, and C

Step-by-step explanation:

Let's simply the equation first

-2(-8 - 4y + 3/4)
16 + 8y - 1 1/2

What did Daniel do wrong?

Well, let's break down what I did and compare it to Daniel.

I multiplied -2 and -8x to get 16x. A negative number times a negative number is positive, and 2 times 8 is 16

Daniel, on the other hand, added the two terms.

The first term should be positive (A)

I multiplied -2 and -4y to get 8y. The same sign rules apply.

Daniel got a negative number, but it is supposed to be positive (B)

I multiplied -2 and 3/4 should be -6/4, which simplifies to -1 2/4 which is further reduced to -1 1/2

Daniel multiplied and simplified incorrectly (C)

-Chetan K

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Select the most accurate statement regarding the normal distribution. Group of answer choices It is always the appropriate distr

PSYCHO15rus [73]

Answer:

There is a 95% chance that values will be within ±2 standard deviations of the mean.

Step-by-step explanation:

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.

The Empirical Rule states that, for a normally distributed random variable:

Approximately 68% of the measures are within 1 standard deviation of the mean.

Approximately 95% of the measures are within 2 standard deviations of the mean.

Approximately 99.7% of the measures are within 3 standard deviations of the mean.

In this question:

According to the empirical rule, 95% of the measures are within 2 standard deviations of the mean. So the correct statement is:

There is a 95% chance that values will be within ±2 standard deviations of the mean.

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3 years ago

tabia stores her hair bands in a cube shaped container. the cube has a volume of 64 cubic inches. What is the lenght of the edge

xeze [42]

Answer:

The length of the edge of the cube = 4 inches

Step-by-step explanation:

* Lets describe the cube

- It has 6 faces all of them are squares

- It has 8 vertices

- It has 12 equal edges

∵ The volume of any formal solid = area of the base × height

∵ The base of the cube is a square

∴ Area base = L × L = L² ⇒ L is the length of the edge of it

∵ All edges are equal in length

∴ Its height = L

∴ The volume of the cube = L² × L = L³

* Now we have the volume and we want to find the

length of the edges

∵ Its volume = 64 inches³

∴ 64 = L³

* Take cube root to the both sides

∴ ∛64 = ∛(L³)

∴ L = 4 inches

* The length of the edge of the cube = 4 inches

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3 years ago

The amount of coffee that a filling machine puts into an 8-ounce jar is normally distributed with a mean of 8.2 ounces and a sta

nordsb [41]

Answer:

73.30% probability that the sampling error made in estimating the mean amount of coffee for all 8-ounce jars by the mean of a random sample of 100 jars will be at most 0.02 ounce

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

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

$\mu = 8.2, \sigma = 0.18, n = 100, s = \frac{0.18}{\sqrt{100}} = 0.018$

What is the probability that the sampling error made in estimating the mean amount of coffee for all 8-ounce jars by the mean of a random sample of 100 jars will be at most 0.02 ounce?

This is the pvalue of Z when X = 8.2 + 0.02 = 8.22 subtracted by the pvalue of Z when X = 8.2 - 0.02 = 8.18. So

X = 8.22

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{8.22 - 8.2}{0.018}$

$Z = 1.11$

$Z = 1.11$ has a pvalue of 0.8665

X = 8.18

$Z = \frac{X - \mu}{s}$

$Z = \frac{8.18 - 8.2}{0.018}$

$Z = -1.11$

$Z = -1.11$ has a pvalue of 0.1335

0.8665 - 0.1335 = 0.7330

73.30% probability that the sampling error made in estimating the mean amount of coffee for all 8-ounce jars by the mean of a random sample of 100 jars will be at most 0.02 ounce

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3 years ago