Data Variability Statistics Example 2

Follow the full solution, then compare it with the other examples linked below.

Example 2

medium
Daily temperatures (°C) for a week: 20, 22, 19, 21, 20, 23, 21. Calculate the mean and describe the variability informally.

Solution

  1. 1
    Step 1: Mean: 20+22+19+21+20+23+217=1467≈20.9°C\frac{20+22+19+21+20+23+21}{7} = \frac{146}{7} \approx 20.9°\text{C}.
  2. 2
    Step 2: The values range from 19 to 23, giving a range of 23−19=4°C23 - 19 = 4°\text{C}.
  3. 3
    Step 3: Most values are within 1–2 degrees of the mean, so variability is low — temperatures were fairly consistent.

Answer

Mean ≈20.9°C\approx 20.9°\text{C}; variability is low (range of 4°C with values clustered near the mean).
Describing variability informally involves looking at how far values typically fall from the centre. Low variability means data points cluster tightly around the mean.

About Data Variability

Data variability describes how much the values in a data set are spread out or clustered together around the center. High variability means values are widely scattered; low variability means they are tightly grouped near the average.

Learn more about Data Variability →

More Data Variability Examples

Example 1 easy

Two classes took the same test. Class A scores: 70, 72, 68, 71, 69. Class B scores: 50, 90, 60, 80,

Example 3 easy

Set X: {5, 5, 5, 5, 5}. Set Y: {1, 3, 5, 7, 9}. Both have mean 5. Which set has zero variability and

Example 4 easy

Team A scores 14, 15, 15, 16, 15 in five games. Team B scores 10, 15, 20, 15, 15. Which team has gre

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