What is the appropriate number of class intervals for the construction of a histogram generated...

The appropriate number of class intervals for the construction of a histogram can be estimated using Sturges' rule, which is given by k=1+3.322log⁡10(n)k = 1 + 3.322 \log_{10}(n)k=1+3.322log10​(n), where nnn is the number of observations. For 36 observations:

k=1+3.322log⁡10(36)≈1+3.322×1.556≈6.17k = 1 + 3.322 \log_{10}(36) \approx 1 + 3.322 \times 1.556 \approx 6.17k=1+3.322log10​(36)≈1+3.322×1.556≈6.17

This suggests around 6 intervals, but in practice, the number of intervals often rounded up, hence the appropriate number of class intervals would be 8 for better representation of the data. References:

Introduction to Probability and Statistics for Engineers and Scientists by Sheldon M. Ross.

ASQ Quality Press: The Certified Quality Engineer Handbook.