Essay About Types Of Design Sampling And Types Of Experimental Hypothesis Testing

Response on Types of Experimental Hypothesis Testing and Types of Design Sampling
This paper is a response to the famous book “Research Methodology: methods and techniques” by C.R.Khotari. In his book, he explains that there are different types of research design. According to him, “when the purpose happens to be an accurate description of a situation or of an association between variables, the suitable design will be one that minimizes bias and maximizes the reliability of the data collected and analyzed”. So, the best research design to be selected in such cases is the experimental hypothesis testing which is defined as a way to carefully plan experiments in advance so that the results are both objective and valid. In addition, Khotari talked about design sampling which is defined as a definite plan determined by the researcher before any data are actually collected for obtaining a sample from a given population. So, I will be trying to explore and explain the different types of experimental hypothesis testing and the different ways of design sampling.             Before I start explaining the different types of designs and design sample, there are some key terms that will be used in this response that has to be explained along with the principles of the experimental hypothesis testing. To begin with, the term independent variable will often be used. It is the treatment or intervention that is being used to bring about change. It is the cause is a cause and effect relationship. Second, we should define the term dependent variable which means the change or difference in behavior that occurs as a result of the independent variable. In order to identify the dependent variable, we should ask the question: what data the researcher is collecting? Also, there are the extraneous or confounding variables which are variables that offer alternative explanations, other than the independent variable, for the results. Finally, the experimental hypothesis testing we are talking about in this paper has three major principles: replication which means that the experiment should be repeated more than once, randomization which means that the experimental units should be chosen randomly, and local control which is the process of minimizing the experimental errors. The next paragraph will discuss the different types of informal design.             One type of the experimental hypothesis testing is the informal design which is composed of three types (before-and-after without control, after-only with control, before-and-after with control). To begin with, in before-and-after design without control, a single group is selected and the dependent variable is measured before the introduction of the treatment. After the introduction of the treatment, the dependant variable is measured again. What we want to know is the effects of the treatment which can be achieved by subtracting the level of the phenomenon after the treatment from the level of the phenomenon before the treatment. The difficulty of this design is the passage of time which is considered as extraneous variation that may affect the treatment effect. In addition, in after-only with control design, two groups or areas (test area and control area) are selected and the treatment is introduced into the test area only. First thing we do is to measure the dependent variable in both areas at the same time and then subtracting the value of the dependent variable in the control area from its value in the test area in order to figure out the treatment impact. In this design, the probability of extraneous variables affecting the treatment is diminished which makes this design superior than before-and-after without control design. Finally, there is the Before-and-after with control design. In this type of design, we have two areas selected and the dependent variable is measured in both areas for the same period of time before the treatment. After that, the treatment is introduced into the test area only, and the dependent variable is measured in both areas for an identical time-period after the introduction of the treatment. Here, the way to determine the treatment effect is by subtracting the change in the dependent variable in the control area from the change in the dependent variable in test area. This design is superior to the above types because it avoids extraneous variations.