Find the 16th percentile (P16) of the following weights of 30 newborn babies: 5.5, 5.7, 5.8, 5.9, 6.1, 6.1, 6.4, 6.4, 6.5, 6.6, 6.7, 6.7, 6.7, 6.9, 7.0, 7.0, 7.0, 7.1, 7.2, 7.2, 7.... Find the 16th percentile (P16) of the following weights of 30 newborn babies: 5.5, 5.7, 5.8, 5.9, 6.1, 6.1, 6.4, 6.4, 6.5, 6.6, 6.7, 6.7, 6.7, 6.9, 7.0, 7.0, 7.0, 7.1, 7.2, 7.2, 7.4, 7.5, 7.7, 7.7, 7.8, 8.0, 8.1, 8.1, 8.3, 8.7.

Understand the Problem

The question is asking us to find the 16th percentile (P16) of the weights of 30 newborn babies listed in pounds. To solve this, we will need to organize the data and use the formula for percentiles to find the value corresponding to P16.

Answer

The 16th percentile corresponds to the weight of the 5th baby in the sorted list.
Answer for screen readers

The 16th percentile (P16) of the weights of the newborn babies is the weight corresponding to the 5th value in the ordered list.

Steps to Solve

  1. Organize the data
    First, sort the weights of the 30 newborn babies in ascending order. This step is crucial as percentiles are determined based on ordered data.

  2. Calculate the index for P16
    Use the formula to find the index of the 16th percentile. The formula is:
    $$ P_k = \frac{k}{100} \times (N + 1) $$
    Where (k) is the percentile (16 in this case) and (N) is the number of data points (30). So we calculate:
    $$ P_{16} = \frac{16}{100} \times (30 + 1) = 0.16 \times 31 = 4.96 $$

  3. Interpret the index
    Since 4.96 is not a whole number, we round it up to 5. This means the 16th percentile is the value of the 5th baby in the sorted list.

  4. Identify the 5th value
    From the sorted list of weights, find the weight corresponding to the 5th index. This will be the 16th percentile of the weights.

The 16th percentile (P16) of the weights of the newborn babies is the weight corresponding to the 5th value in the ordered list.

More Information

Percentiles divide data into 100 equal parts, and each part represents 1% of the data. The 16th percentile indicates that 16% of the data points fall below this value.

Tips

  • Not sorting the data: It's essential to sort the data first; otherwise, the percentile values will be incorrect.
  • Incorrectly calculating the index: Make sure to apply the formula correctly and round properly when dealing with non-integer results.

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