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AVprozaik [17]
3 years ago
8

Jackson is comparison shopping for orange juice. He created a table to help him decide which package was the best deal.Orange Ju

ice Cost by PackagePackageCostCost per ounce10 oz bottle$1.99$0.19959 oz bottle$3.33$0.056489 oz bottle$4.99$0.0561Case of 2410 oz bottles$34.99$0.145864 oz carton$3.60$0.05625Jackson claims that the order of the best deal to the worst deal (based on cost/oz) is 10 oz bottle, 89 oz bottle, 59 oz bottle, case of 24 10 oz bottles, and 64 oz carton. Which statement about Jackson’s claim is true?Jackson is correct because he used the length of each decimal to compare the different costs. For example, 0.149 < 0.1457 < 0.05625.Jackson is correct because he compared values in equal place values to compare only the decimals with the same length. For example, 0.0561 < 0.0564 < 0.05625.Jackson is incorrect because he should compare the values in equal place values to compare all the decimals, not just those of the same length. For example, 0.0561 < 0.05625 < 0.0564.Jackson is incorrect because the case of 24 oz bottles is less per ounce than the 59 oz bottle and the 89 oz bottle. For example, 0.1457 < 0.0561 < 0.0564.
Mathematics
1 answer:
Maksim231197 [3]3 years ago
5 0

Answer:

b

Step-by-step explanation:

mark me brainlist

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A bottling company uses a filling machine to fill cans with an energy drink. The cans are supposed to contain 250 ml. The machin
sveta [45]

Answer:

a) Mean 250 ml, standard deviation 1.2247 ml.

b) 74.14% probability that the volume of a single randomly chosen can differs from the target value by 1 ml or more.

c) 41.22% probability that the sample mean volume of a random sample of 6 cans differs from the target value by 1 ml or more

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 question:

\mu = 250, \sigma = 3

a) Assume that the process mean is exactly equal to the target value, that is μ=250. What will be the mean and standard deviation of the sampling distribution of the sample mean x?

By the Central Limit Theorem, the mean is 250 ml and the standard deviation is s = \frac{3}{\sqrt{6}} = 1.2247 ml.

b) What is the probability that the volume of a single randomly chosen can differs from the target value by 1 ml or more?

Greater than 250 + 1 = 251 or lesser than 250 - 1 = 249.

Since the normal distribution is symmetric, these probabilities are the same, so we can find one of them and multiply by 2.

Lesser than 249:

pvalue of Z when X = 249.

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

Z = \frac{249 - 250}{3}

Z = -0.33

Z = -0.33 has a pvalue of 0.3707

0.3707*0.2 = 0.7414

74.14% probability that the volume of a single randomly chosen can differs from the target value by 1 ml or more.

c) What is the probability that the sample mean volume of a random sample of 6 cans differs from the target value by 1 ml or more?

Since more than 1 can, we use the Central Limit Theorem.

The probability follows the same logic as b.

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

By the Central Limit Theorem

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

Z = \frac{249 - 250}{1.2247}

Z = -0.82

Z = -0.82 has a pvalue of 0.2061

2*0.2061 = 0.4122

41.22% probability that the sample mean volume of a random sample of 6 cans differs from the target value by 1 ml or more

5 0
4 years ago
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