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First Quartile Calculator

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The First Quartile Calculator helps you find the 25th percentile of an ordered dataset. This means it calculates the value below which 25% of the data points lie. The first quartile, also known as Q1, is essential for understanding data spread, spotting outliers, and performing statistical analysis in fields like finance, education, and research.

This calculator falls under the category of Statistical and Data Analysis tools. It simplifies the process by avoiding manual ranking and interpolation steps, especially helpful for large or uneven datasets.

Formula of First Quartile Calculator

First Quartile

Where:
n = total number of observations in the sorted dataset

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Steps:

  1. Sort the data in ascending order.
  2. Calculate position P:
    P = (n + 1) × 1/4

If P is an integer:
Q1 = value at position P

If P is a decimal (e.g., 3.25):
Q1 = Value at floor(P) + (decimal part × (Value at ceiling(P) − Value at floor(P)))

This interpolation step ensures you get a more accurate Q1 when P falls between two values.

Reference Table

Number of Data Points (n) Position Formula (Q1) Action Needed
4 (4 + 1) × 0.25 = 1.25 Interpolate between 1st and 2nd
5 (5 + 1) × 0.25 = 1.5 Interpolate between 1st and 2nd
7 (7 + 1) × 0.25 = 2.0 Use value at position 2
10 (10 + 1) × 0.25 = 2.75 Interpolate between 2nd and 3rd
12 (12 + 1) × 0.25 = 3.25 Interpolate between 3rd and 4th

This table helps users quickly determine the interpolation step required without recalculating from scratch.

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Example of First Quartile Calculator

Dataset: 3, 7, 8, 12, 13, 14, 18, 21, 23, 27
Step 1: n = 10
Step 2: Calculate position: P = (10 + 1) × 1/4 = 11 × 0.25 = 2.75

Step 3: Find the values at position 2 and 3 in the sorted data:
Value at position 2 = 7
Value at position 3 = 8

Now interpolate:
Q1 = 7 + (0.75 × (8 − 7)) = 7 + 0.75 = 7.75

So, the first quartile is 7.75.

Most Common FAQs

What is the first quartile used for?

The first quartile helps you understand the lower 25% of your data. It’s useful for measuring data spread and detecting skewness and outliers in datasets.

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Does Q1 always fall between two numbers?

Not always. If the position (n + 1) × 1/4 gives a whole number, Q1 is the value at that position. Otherwise, interpolation is used.

Can this calculator work with both odd and even number of data points?

Yes. It works regardless of whether the total number of data points is odd or even. The interpolation method ensures accuracy in all cases.

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