Do you believe that the US should convert to the metric system explain why or why notâ

Ghana is a very beautiful country even in the history, Ghana's empire was a very legendary in Africa. There are many countries like Ghana in Africa like Benin, Sierra Leone, Mali, Songhai, Zimbabwe and Togo also Ivory Coast and Niger

5 0

3 years ago

4x find the degree with steps

Alex787 [66]

9514 1404 393

Answer:

1

Step-by-step explanation:

The term has 1 variable, which has no exponent shown. When the exponent is not shown, it is understood to be 1. The degree of the term is the exponent of this single variable, so the degree is 1.

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<em>Additional comment</em>

If the term is a product of more than one variable, the degree is the sum of their exponents.

3 0

2 years ago

A tobacco company claims that the amount of nicotene in its cigarettes is a random variable with mean 2.2 and standard deviation

Aleksandr-060686 [28]

Answer:

0% probability that the sample mean would have been as high or higher than 3.1 if the company’s claims were true.

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