What is the general rule of thumb for selecting the number of intervals in a histogram?

What is the general rule of thumb for selecting the number of intervals in a histogram?

• A. Square root of the number of observations
• B. Number of observations
• C. Log of observations
• D. Constant 10

Answer: (A)

When deciding how many intervals to display in a histogram, you want enough bars to reveal the shape of the data without letting random noise create false detail. A simple rule of thumb is to use about the square root of the number of observations as the number of bins. This scales with sample size so larger datasets get more bins, but not so many that the histogram becomes noisy. For example, with 100 observations you’d typically use around 10 bins; with 1,000 observations you’d use about 31 bins. This balances viewable detail with clarity, making the distribution easier to interpret. Other methods exist, but this easy-to-remember guideline provides sensible, scalable results.

When deciding how many intervals to display in a histogram, you want enough bars to reveal the shape of the data without letting random noise create false detail. A simple rule of thumb is to use about the square root of the number of observations as the number of bins. This scales with sample size so larger datasets get more bins, but not so many that the histogram becomes noisy. For example, with 100 observations you’d typically use around 10 bins; with 1,000 observations you’d use about 31 bins. This balances viewable detail with clarity, making the distribution easier to interpret. Other methods exist, but this easy-to-remember guideline provides sensible, scalable results.