Location-scale problems arise in many cases, such as, bioinformatics, climate dynamics, finance and medicine (Marozzi, 2013). This research focuses on developing tests to determine whether one or more treatment effects differ from the control. It will be assumed that when a treatment effect differs from the control effect, it is greater either in mean or variance (simple tree alternative). It is also assumed that a treatment effect difference results in the change of the location and / or scale parameters between two population distributions. This research will consider the area of nonparametric tests when determining whether one or more of the treatment effects is larger than the control. Five nonparametric tests are proposed for the simple tree alternative. A simulation study will be conducted to determine how well the proposed tests maintain their significance levels. Powers will be estimated for the proposed tests under a variety of conditions for two, three and four populations. Three different types of variable parameters will be considered. The first type considered is when the location parameters are different, and the scale parameters are equal. The second type considered is when the location parameters are equal, and the scale parameters are different. The final type considered is when the location and scale parameters are both different. Results will be given as far as which test does better under certain conditions.