Three-factor experimental design as a tool in Applied Statistics

Abstract

The purpose of this research is the implementation of Three-factor experimental design a as a tool in Applied Statistics in purpose of definition of indicators of the effectiveness of reducing stress levels and anxiety in students during meditation training Three-factor experimental design and yoga exercise training. Using this three-factor model three parameters were monitored: blood pressure, duration of sleeping, and smoking. This system of indicators is called a three-factor experimental design with two levels of variation (2^3) for the process of stress and anxiety. A way to obtain simplified models is using full factorial designs, which are important means to evaluate the influence of the factors on response. All 30 students-volunteers have been randomly selected, in the three-factor experiment, and analyzed, and in each case, regardless of gender, the effect of the factors. The result obtained from these analyses using the three-factor experiment were very similar for all the respondents. By applying this model, it shows highest influence has a coefficient of factor smoking, then hours of sleeping on response y (stress and anxiety). This model is a systematic method to determine the relationship between factors affecting a process and the output of that process. In other words, it is used to find cause-and-effect relationships. This information is needed to manage process inputs to optimize the output.