In hypothesis-testing research studies, also known as experimental studies, the researcher generally tests the hypotheses of causal relationships among variables. Besides, such type of studies needs those kinds of procedures, which will not only reduce the bias and increase reliability, but will also approve the drawing inferences about causality. Hence, when we discuss about the research design in such studies, we usually mean the experimental designs.
Experimental designs were discovered and developed by Professor R. A. Fisher, who was working at the Rothamsted Experimental Station, at the Centre for Agricultural Research in England. In fact, the study of experimental designs originated in agricultural research. Professor Fisher divided the agricultural fields/plots into different blocks and conducted experiments in each of them. Consequently, whatever information was collected from this, he found them to be very reliable. In this way, he was inspired to develop certain experimental designs to test the hypotheses about scientific investigations. In recent time, the experimental designs are being used in researches related to phenomena of several disciplines. Besides, since experimental designs originated in the context of agricultural operations, we still use, although in a technical sense, several agricultural terms, such as, treatment, yield, plot, block, etc., in the experimental designs.
Once the data analyzing process is complete, the researcher is ready to test the hypothesis, which was formulated earlier. Hypothesis testing involves systematic methods, which are used to evaluate the data and aid the decision-making process. Various statistical measures are used to test the data: parametric analysis (Ttest, ANOVA, Regression, etc.) and non-parametric analysis (ChiSquare, Kruskal Wallis, Mann“Whitney, etc.). These testing methods differ depending on the types of measurements and tools used for those measurements. One must choose the appropriate statistical method in order to obtain meaningful results. Based on the results of the calculations, hypothesis testing will result in either the hypothesis being accepted or rejected. The hypothesis is ruled out or modified if its predictions are incompatible with the experimental tests.
Generalizations and Interpretation
This is the final stage of the scientific research process. While testing, if the hypothesis is upheld several times, the researcher may form generalizations, i.e., build theories based on it. Generalizations give an indication of the actual achievement of the researcher. In case, the researcher had no hypothesis while starting the experiment he tries to explain his findings on the basis of some already established theory. This is known as interpretation. It is a process, which makes it easier to understand the factors that explain what was observed by the researcher during the course of his study. It also provides a theoretical conception, which serves as a guide. Interpretation may lead to new questions, thus leading to further researches.