The histogram has all its bin widths equal to some non-random number arbitrary set by an analyst (EBWH). In the result, particular bin counts are random variables. This paper presents also a histogram that is constructed in a converse manner. Bin counts are all equal to some non-random number arbitrary set by an analyst (EBCH). In the result, particular bin widths are random variables. The first goal of the paper is a choose of constant bin width (of bin numbers k) in the EBWH, which maximize the similarity measure in the Monte Carlo simulation. The second goal is a choose of constant bin count in the EBCH, which maximize the similarity measure in the Monte Carlo simulation. The third goal is to present similarity measures between empirical and theoretical data. The fourth goal is the comparative analysis of two histogram methods by means of the frequency formula. The first additional goal is a tip how to proceed in EBCH when modulo(n,k)≠0. The second additional goal is the software in the form of a Mathcad file with the implementation of EBWH and EBCH.

直方图的所有bin宽度等于分析人员（EBWH）任意设置的一些非随机数。结果，特定的bin计数是随机变量。本文还介绍了以相反方式构造的直方图。Bin计数都等于分析人员（EBCH）设置的任意非随机数。结果，特定的条带宽度是随机变量。本文的首要目标是选择恒定的箱宽（箱号k）中的数据，从而在蒙特卡洛模拟中最大化相似度。第二个目标是在EBCH中选择恒定仓数，这可以最大化Monte Carlo模拟中的相似度。第三个目标是提出经验数据和理论数据之间的相似性度量。第四个目标是通过频率公式比较两种直方图方法。第一个附加目标是提示当modulo（n，k）≠0时如何在EBCH中进行。第二个附加目标是Mathcad文件形式的软件，其中包含EBWH和EBCH的实现。