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spayn [35]
3 years ago
4

Match the values with the statistical measures for these data points. 20, 20, 21, 22, 23, 23, 24, 24, 25, 25, 26, 26 Tiles 22.5

25 23.5 21.5 23 Pairs upper quartile lower quartile median
Mathematics
2 answers:
ozzi3 years ago
8 0

Answer:

20,20,21,22,23,23,24,24,25,25,26,26

Step-by-step explanation:

median (middle number) is (23 + 24) / 2 = 47/2 = 23.5 <== median

Q1 = (21 + 22) / 2 = 43/2 = 21.5 <== lower quartile

Q3 = (25 + 25) / 2 = 50/2 = 25 <== upper quartile

Naya [18.7K]3 years ago
4 0
20,20,21,22,23,23,24,24,25,25,26,26

median (middle number) is (23 + 24) / 2 = 47/2 = 23.5 <== median

Q1 = (21 + 22) / 2 = 43/2 = 21.5 <== lower quartile
Q3 = (25 + 25) / 2 = 50/2 = 25 <== upper quartile
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Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

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 normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

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

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Central Limit Theorem

The Central Limit Theorem establishes 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.

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This means that n = 46

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

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Z = -1.38

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