Abstract
From the perspectives of the philosophy of science and statistical inference, we discuss the challenges of making prescriptive statements in quantitative research articles. We first consider the prescriptive nature of educational research and argue that prescriptive statements are a necessity in educational research. The logic of deduction, abduction, and induction in philosophy of science are briefly reviewed, and the logic of prescriptive statement is specifically considered. The inductive nature of statistical inference is examined for both classical frequentist statistics and Bayesian statistics. To conclude our discussion, we recommend conducting replications and building “research programs” in educational research. We also make recommendations on what to write in the discussion section and what evidence is required to make an appropriate prescriptive statement.
Similar content being viewed by others
References
Bacon, F. (1620/1960). The new organon, and related writings. New York: Liberal Arts.
Berliner, D. C. (2002). Educational research: the hardest science of all. Educational Researcher, 31(8), 18–20.
Camilleri, S. F. (1962). Theory, probability, and induction in social research. American Sociological Review, 27, 170–178.
Campbell, D. T., & Stanley, J. C. (1966). Experimental and quasi-experimental designs for research. Chicago: Rand McNally.
Cantrell, S. C., Janice, F. A., Carter, J. C., Rintamaa, M., & Madden, A. (2010). The impact of a strategy-based intervention on the comprehension and strategy use of struggling adolescent readers. Journal of Educational Psychology, 102, 257–280.
Cohen, J. (1990). Things I have learned (so far). The American Psychologist, 45, 1304–1312.
Cohen, J. (1994). The earth is around (p < .05). The American Psychologist, 49, 997–1003.
Collins, H. M. (1992). Changing order: Replication and induction in scientific practice with a new afterword. Chicago: The University of Chicago Press.
Dawson, C. (1994). Human resource accounting: From prescription to description? Management Decision, 32(6), 35–40.
de Regt, H. (1994). Representing the world by scientific theories: The case for scientific realism. Tilburg, Netherlands: Tilburg University Press.
DeFinetti, B. (1974). Theory of probability. New York: Wiley.
Dettmers, S., Trautwein, U., Lüdtke, O., Kunter, M., & Baumert, J. (2010). Homework works if homework quality is high: Using multilevel modeling to predict the development of achievement in mathematics. Journal of Educational Psychology, 102, 467–482.
Dewey, J. (1938). Logic: The theory of inquiry. New York: H. Holt and Company.
Dienes, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference. New York: Palgrave Macmillan.
Edwards, W., Lindman, H., & Savage, L. J. (1963). Bayesian statistical inference for psychological research. Psychological Review, 70, 193–242.
Fahs, P. S., Morgan, L. L., & Kalman, M. (2003). A call for replication. Journal of Nursing Scholarship, 35, 67–72.
Feuer, M. J., Towne, L., & Shavelson, R. J. (2002). Scientific culture and educational research. Educational Researcher, 31(8), 4–14.
Fisher, R. A. (1955). Statistical methods and scientific induction. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 17, 69–78.
Fisher, R. A. (1956). Statistical methods and scientific inference. New York: Hafner.
Fritz, C. A. (1960). What is induction? The Journal of Philosophy, 57, 126–138.
Good, I. J. (1984). Review: A Bayesian approach in the philosophy of inference. The British Journal for the Philosophy of Science, 35, 161–166.
Greenland, S. (1998). Induction versus Popper: Substance versus semantics. International Journal of Epidemiology, 27, 543–548.
Hausman, C. R. (1993). Charles S. Peirce’s evolutionary philosophy. Cambridge: Cambridge University Press.
Hawthorne, J. (1993). Bayesian induction is eliminative induction. Philosophical Topics, 21, 99–138.
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando: Academic.
Henson, R. K. (2006). Effect size measures and meta-analytic thinking in counseling psychology research. The Counseling Psychologist, 34, 601–629.
Hume, D. (1777/1912). An enquiry concerning human understanding, and selections from a treatise of human nature. Chicago: Open Court Publishing.
Jaynes, E. T. (1979). Review of the book Inference, method, and decision: Towards a Bayesian philosophy of science. Journal of the American Statistical Association, 74, 740–741.
Jeffreys, H. (1939). Theory of probability. Oxford, England: Clarendon.
Johnson-Laird, P. N. (1994). A model theory of induction. International Studies in the Philosophy of Science, 8, 5–29.
Josephson, J. R., & Josephson, S. G. (Eds.). (1994). Abductive inference: Computation, philosophy, technology. Cambridge: Cambridge University Press.
Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56, 746–759.
Kline, R. B. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. Washington: American Psychological Association.
Lakatos, I. (1968–1969). Criticism and the methodology of scientific research programs. Proceedings of the Aristotelina Society, New Series, 69, 149–186.
Lakatos, I. (1970). Falsification and the methodology of scientific research programs. In I. Lakatos & A. Musgrove (Eds.), Criticism and the growth of knowledge (pp. 91–196). Cambridge: Cambridge University Press.
Locke, E. A. (2007). The case for inductive theory building. Journal of Management, 33, 867–890.
Neyman, J. (1957). “Inductive behavior” as a basic concept of philosophy of science. Review of the International Statistical Institute, 25, 7–22.
Niiniluoto, I. (1999). Defending abduction. Philosophy of Science, 66(Suppl), 436–451.
Peirce, C. S. (1877). The fixation of belief. Popular Science Monthly, 12, 1–15.
Peirce, C. S. (1934/1960). Collected papers of Charles Sander Peirce. Cambridge: Harvard University Press.
Popper, K. R. (1959). The logic of scientific discovery. New York: Harper & Row.
Powell, D. R., Diamond, K. E., Burchinal, M. R., & Koehler, M. J. (2010). Effects of an early literacy professional development intervention on head start teachers and children. Journal of Educational Psychology, 102, 209–312.
Reese, H. W. (1999). Strategies for replication research exemplified by replications of the Istomina study. Developmental Review, 19, 1–30.
Rindskopf, D. M. (1997). Testing “small”, not null, hypotheses: Classical and Bayesian approaches. In L. L. Harlow, S. A. Mulaik, & J. H. Steiger (Eds.), What if there were no significance tests? (pp. 319–332). Mahwah: Lawrence Erlbaum Associates.
Rosenkrantz, R. D. (1977). Inference, method, and decision: Towards a Bayesian philosophy of science. Boston: D. Reidel Publishing.
Rothman, K. J., & Greenland, S. (1997). Modern epidemiology (2nd ed.). Philadelphia: Lippincott.
Schilpp, P. A. (Ed.). (1974). The philosophy of Karl Popper. LaSalle: Open Court Press.
Schmidt, S. (2009). Shall we really do it again? The powerful concept of replication is neglected in the social sciences. Review of General Psychology, 13, 90–100.
Searle, J. R. (1964). How to derive “ought” from “is”. The Philosophical Review, 1, 43–58.
Sen, A. K. (1967). The nature and classes of prescriptive judgments. The Philosophical Quarterly, 17(46), 46–62.
Serlin, R. C. (1987). Hypothesis testing, theory building, and the philosophy of science. Journal of Counseling Psychology, 34, 365–371.
Shuell, T. J. (1982). Developing a viable link between scientific psychology and educational practices. Instruction Science, 11, 155–167.
Simon, H. A. (1996). The sciences of the artificial (3rd ed.). Cambridge: MIT Press.
Sun, S., Pan, W., & Wang, L. (2010). A comprehensive review of effect size reporting and interpreting practices in academic journals in education and psychology. Journal of Educational Psychology, 102, 989–1004.
Staat, W. (1993). On abduction, deduction, induction and the categories. Transactions of the Charles S. Peirce Society, 29, 225–237.
Thompson, B. (1993). The use of statistical significance tests in research: Bootstrap and other alternatives. The Journal of Experimental Education, 61, 361–377.
Thompson, B. (1996). AERA editorial policies regarding statistical significance testing: Three suggested reforms. Educational Researcher, 25(2), 26–30.
Thompson, B. (1997). Editorial policies regarding statistical significance tests: Further comments. Educational Researcher, 26(5), 29–32.
Thompson, B. (2002). What future quantitative social science research could look like: Confidence intervals for effect sizes. Educational Researcher, 31, 25–32.
Thompson, B. (2007). Effect sizes, confidence intervals, and confidence intervals for effect sizes. Psychology in the Schools, 45(2), 423–432.
Thompson, B. (2008). Computing and interpreting effect sizes, confidence intervals, and confidence intervals for effect sizes. In J. W. Osborne (Ed.), Best practices in quantitative methods (pp. 246–262). Thousand Oaks: Sage.
Trundle, R. (1994). Ancient Greek philosophy: Its development and relevance to our time. Brookfield: Avebury.
Tsang, E. W. K. (1997). Organizational learning and the learning organization: A dichotomy between descriptive and prescriptive research. Human Relations, 50, 73–89.
von Mises, R. (1957). Probability, statistics, and truth (2nd ed.). New York: Dover.
Wainer, H. (2010). 14 conversations about three things. Journal of Educational and Behavioral Statistics, 35, 5–25.
Yu, C. H. (2006). Philosophical foundations of quantitative research methodology. Toronto: University Press of America.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sun, S., Pan, W. The Philosophical Foundations of Prescriptive Statements and Statistical Inference. Educ Psychol Rev 23, 207–220 (2011). https://doi.org/10.1007/s10648-011-9157-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10648-011-9157-8