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3 years ago

I need help with this plz

Mathematics

1 answer:

Ksju [112]3 years ago

5 0

Answer:

The correct answer is D. 10.

Step-by-step explanation:

If Brandy earns 2 stars for every goal, and she scored 8 goals, then we need to multiply 8 by 2.

8 x 2 = 16

She looses 1/2 a star for every miss, and she missed the goal 12 times. Therefore, we need to multiply 1/2 by 12.

12 x 1/2 = 6

Therefore, Brandy lost 6 stars.

Now, we need to subtract the amount of stars Brandy earned by the amount that she lost.

16 - 6 = 10

Therefore, the correct answer is D. 10.

Hope this helps! :D

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Answer:

89.44% probability that less than 80% of the sample would report eating healthily the previous day

Step-by-step explanation:

We use the binomial approximation to the normal to solve this question.

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:

$p = 0.78, n = 675$

$\mu = E(X) = np = 675*0.78 = 526.5$

$\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{675*0.78*0.22} = 10.76$

What is the approximate probability that less than 80% of the sample would report eating healthily the previous day?

This is the pvalue of Z when $X = 0.8*675 = 540$ . So

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

$Z = \frac{540 - 526.5}{10.76}$

$Z = 1.25$

$Z = 1.25$ has a pvalue of 0.8944

89.44% probability that less than 80% of the sample would report eating healthily the previous day

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3 years ago

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jek_recluse [69]

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3 years ago

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pantera1 [17]

Answer:

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Step-by-step explanation:

The empirical probability, also called experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, not in a theoretical sample space but in an actual experiment.

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Hope this Helps!!!

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3 years ago