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To determine the number of values in the upper quartile of a data set that contains 16 data values, follow these steps:
1. Understand the concept of the upper quartile: The upper quartile (also known as the third quartile) is the value below which 75% of the data falls. Therefore, it represents the top 25% of the data.
2. Calculate the number of values in the upper quartile: To find out how many data values fall into this upper quartile, you need to find 25% (or one-quarter) of the total number of data values.
3. Perform the calculation: Since the data set has 16 values, you calculate 25% of 16.
- 25% of 16 can be calculated as [tex]\(\frac{25}{100} \times 16\)[/tex].
4. Simplify the calculation:
- [tex]\(\frac{25}{100} = 0.25\)[/tex].
- Multiplying 16 by 0.25 gives:
[tex]\[ 0.25 \times 16 = 4 \][/tex]
Therefore, the number of values in the upper quartile is [tex]\(4.0\)[/tex].
1. Understand the concept of the upper quartile: The upper quartile (also known as the third quartile) is the value below which 75% of the data falls. Therefore, it represents the top 25% of the data.
2. Calculate the number of values in the upper quartile: To find out how many data values fall into this upper quartile, you need to find 25% (or one-quarter) of the total number of data values.
3. Perform the calculation: Since the data set has 16 values, you calculate 25% of 16.
- 25% of 16 can be calculated as [tex]\(\frac{25}{100} \times 16\)[/tex].
4. Simplify the calculation:
- [tex]\(\frac{25}{100} = 0.25\)[/tex].
- Multiplying 16 by 0.25 gives:
[tex]\[ 0.25 \times 16 = 4 \][/tex]
Therefore, the number of values in the upper quartile is [tex]\(4.0\)[/tex].
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