English: At the end of the novel, the creature confesses that he feels . . . A happiness that Frankenstein is dead. B sorrow for the suffering he caused. C sympathy for Walton and his crew. D anger because he never had a friend.

At the end of the novel, the creature confesses that

Ответ:

castiaulii16

21.01.2022

English

At the end of the novel, the creature confesses that he feels sorrow for the suffering he caused.

Option B

Explanation:

Frankenstein is a novel written by Mary Shelley. In the novel he was a doctor. After the death of Frankenstein Monster was so depressed and he wanted to commit killing himself. There was a fear in the mind of Frankenstein. He thought the creature may commit killing himself.

Monster was created by Victor as he was also thoughtful about the Monster. At the end of the novel the creature confesses that he feels very sorrow for Frankenstein and he is feeling hopeless because of not getting female partner.

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Ответ:

JGottem6489

09.03.2023

English

0.02% probability that the average amount billed on the sample bills is greater than $500.

Step-by-step explanation:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $\frac{\sigma}{\sqrt{n}}$ .

Normal probability distribution

Problems of normally distributed samples 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.

In this problem, we have that:

$\mu = 465, \sigma = 300, n = 900, s = \frac{300}{\sqrt{900}} = 10$ .