The scientific method is the instrument by which humanity is able to overcome the chains of subjectivism, turn from the shadows of pattern and prediction, and face the blinding light of causality. As to psychology, the scientific method is the main avenue through which research concerning cognition, behavior, and mental functionality is carried out; and statistics is the means through which patterns and predictions are formulated, to the end of viable hypotheses (i.e. hypotheses that elucidate causality). However, incumbent on the proper understanding of the interrelatedness of research, statistics, and psychology, is a thorough treatment of the scientific method, the consideration of the applicability of primary and secondary data to research, and full comprehension of the function that statistics plays in scientific research.
Before the advent of the scientific method, humans relied primarily on personal introspection, clever reasoning, and pattern predictions to understand the world around and within us. The scientific method offered the first venue in which objective, verifiable truths could be discovered and duplicated. The basic steps in the scientific method, more categories than a set of rigid procedures, are: make an observation about a scientific problem, create a hypothesis, test the hypothesis, record the results, and finally draw conclusions about the results (Cowens, 2006). The cardo duplex, or cardinal point, of the scientific method, is the hypothesis synthesizing stage. A scientific hypothesis must propose the elucidation of causality, not simply the prediction of future patterns (McPherson, 2001). It is imperative that a scientific hypothesis uncover the reason behind the pattern (hypothetico-deductive method), rather than merely predict the statistical likelihood of the future occurrence of some pattern (statistical hypothesis). It is also important to revise a hypothesis and retest it if the results of the experiment do not match the original hypothesis. In this manner, research is carried out in the area of psychology, and indeed all areas of respectable science, to the conclusion of scientific truths that tell us something about our world.
In the realm of psychology, primary data is the coveted aunt and secondary data the reluctant uncle of everyday research. Primary data comprises that area of research which is carried out first hand and for the exclusive purpose of the current study; whereas, secondary data is basically the use of someone else’s primary data. Even though primary data is preferable to secondary data in psychological research, researchers do not always have the luxury of financing their own surveys, case studies, and cross-disciple research (Rabianski, 2003). In these cases, it is more pragmatic to use other studies, sometimes many studies, which have been carried out on other related subjects in order to reinforce or disprove a possible hypothesis. For instance, a study was carried out by Graeme Hawthorne (2003) on the subject of the health-related quality of life (HRQoL) field in order to establish the test-retest reliability of Assessment of Quality of Life (AQoL) instrument utility scores. During this study Hawthorne used mostly primary data, with the obvious exception of references to past research carried out on the subject, to determine the statistical probability of test-retest reliability concerning the AQoL instrument utility scores. In all, primary data is the preferred means of investigation, but when primary data is not available or impractical secondary data is the most viable alternative for the scientific research of psychology.
In relation to the scientific method, statistics is fundamental in the formulation of viable scientific hypotheses, not that statistics can prove causality, but that statistics can illuminate patterns. These patterns can then be used as a basis for the prediction of possible underlying causes. Strictly speaking, statistics is the, “…branch of mathematics that focuses on the organization, analysis, and interpretation of a group of numbers” (Aron, Aron, & Coups, 2006, p. 2). Statistics can be both primary and secondary data and can be divided into two separate types: descriptive and inferential statistics. Put plainly, descriptive statistics is the representation of current data and inferential statistics is the use of current data to predict future data. Furthermore, statistics are mostly applied to quantitative research, research concerned with design replication, objectivity, and reliability/validity of design; while, at the same time playing a supportive role in qualitative research, or research utilizing introspection and generalization (Schumacker, 2000). As a whole, statistics is the catalyst by which hypothesis generation occurs and one of the primary methods of quantitative research.
In conclusion, statistics perform a vital role in the scientific method; that of instigator in chief, bringing to light patterns that elucidate hypothesized causality. Furthermore, the scientific method is the main instrument through which scientific research is carried out in the area of psychology. Scientific research can also be categorized as qualitative or quantitative, statistical or implied, respectively; and even though primary data is preferred because of its direct applicability, secondary data is the unwelcome, yet necessary means of a great deal of scientific research.
Aron, A., Aron, E., & Coups, E. (2006). Statistics for psychology (4th ed.). Upper Saddle River, NJ: Pearson/Allyn Bacon.
Cowens, J. (2006). The scientific method. Teaching PreK-8, 37(1), 42.
Hawthorne, G. (2003). The effect of different methods of collecting data: Mail, telephone and filter data collection issues in utility measurement. Quality of Life Research, 12(8), 1081.
McPherson, G. R. (2001). Teaching & learning the scientific method. The American Biology Teacher, 63(4), 242.
Rabianski, J. S. (2003). Primary and secondary data: Concepts, concerns, errors, and issues.
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