A common assumption in many statistical data analyses is that the distribution of observations is normal. However, this assumption is often violated in real data analysis. For this purpose, flexible distributions have been proposed as an alternative to the normal distribution. In this regard, we can mention the slash and hump-slash distributions, which have received much attention from researchers in the last decade. The slash distribution is known as a heavy-tailed and symmetric distribution in robust studies. However, considering that in experimental examples, there are many cases when symmetric distributions are not suitable for fitting data, the study of distributions in the hump state is also of particular importance, hence the introduction of hump generalizations of the slash distribution has attracted the attention of researchers. Applications of this distribution are commonly found in complex multi-component systems such as environmental systems, economics, sociology, finance, etc. In this article, we examine the Chole-Slash distribution and its properties using real data sets and examine the importance of using this distribution in regression models.