Which is more 3 liters or 2997 millilliters

Consider a binomial distribution of 200 trials with expected value 80 and standard deviation of about 6.9. Use the criterion tha

zavuch27 [327]

Answer:

120 has a z-score higher than 2.5. So yes, it would be unusual to have more than 120 successes out of 200 trials.

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

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.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

In this problem, we have that:

$\mu = 80, \sigma = 6.9$

Use the criterion that it is unusual to have data values more than 2.5 standard deviations above the mean or 2.5 standard deviations below the mean

This means that z-scores higher than 2.5 or lower than -2.5 are considered unusual.

Would it be unusual to have more than 120 successes out of 200 trials

We have to find the Z-score of X = 120.

So

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

$Z = \frac{120 - 80}{6.9}$

$Z = 5.8$

120 has a z-score higher than 2.5. So yes, it would be unusual to have more than 120 successes out of 200 trials.

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$SE=\frac{s}{\sqrt[]{n}}$ $\begin{gathered} \text{ Where } \\ SE=\text{ the standard error} \\ s=\text{ the sample standard deviation} \\ n=\text{ the sample size} \end{gathered}$

In this case,