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Empirical Testing - Definition

Written by Jason Gordon

Updated at December 19th, 2020

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Empirical Testing Definition

Empirical testing is a research method that employs direct and indirect observation and experience.

A Little More on What is Empirical Testing

Empirical evidence (the file of one's direct observations or reports) is an effective research method, as the results can be analyzed quantitatively or qualitatively. Different fields and study use unique research designs suitable to their studies. In some fields, quantitative studies begin with a research question that is examined with different techniques such as experimentation. A researcher uses a particular theory relating to a subject of research and develops hypotheses upon that theory. Then the researcher derives many predictions from the hypothesis or research question. Those predictions can then be examined with a suitable test. The hypothesis will be accepted or rejected based upon the results of hypothesis or research question. Scientific research The empirical method allows a scientific researcher to verify the results of research with the help of statistical tools. Common statistical tools include: regression, risk coefficient, t-test, chi square, and different forms of ANOVA (analyses of variance).

Empirical Cycle

Observation: Observation is the process of identifying the problem and its causes. Induction: The idea or hypothesis is developed on the basis of observation. Deduction: Deduction is the process to formulate experiments to check the hypothesis Testing: Testing is the technique used to check the hypotheses and data related to hypothesis. Evaluation: In this stage, results are interpreted explanations are presented.

References for Empirical Research

https://en.wikipedia.org/wiki/Empirical_researchhttps://financial-dictionary.thefreedictionary.com/empirical+testinghttps://philpapers.org/browse/empirical-testing-in-economics

Academic Research on Empirical Testing

  • On the limitations of government borrowing: A framework forempirical testing, Hamilton, J. D., & Flavin, M. (1985). This paper seeks to distinguish empirically between two views on the limitations of government borrowing. This paper shows that distinguishing between these possibilities is mathematically equivalent to testing whether a continuing currency inflation might be fueled by speculation alone or is instead driven solely by economic fundamentals.
  • Empirical testingof a model of online store atmospherics and shopper responses, Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2003).Psychology & marketing,20(2), 139-150. This study empirically tests a model that proposes that the atmospheric cues of the online store influence shoppers' emotional and cognitive states, which then affect their shopping outcomes.
  • Comparison ofempirical testingand walkthrough methods in user interface evaluation, Karat, C. M., Campbell, R., & Fiegel, T. (1992, June). InProceedings of the SIGCHI conference on Human factors in computing systems(pp. 397-404). ACM. This study investigates the relative effectiveness of empirical usability testing and individual and team walkthrough methods in identifying usability problems in two graphical user interface office systems. Results from cost-effectiveness data show that empirical testing required the same or less time to identify each problem when compared to walkthroughs.
  • Empirical testingof real optionpricing models, Quigg, L. (1993). The Journal of Finance,48(2), 621-640. This research is the first to examine the empirical predictions of a real option-pricing model using a large sample of market prices. We find empirical support for a model that incorporates the option to wait to develop land. The option model has explanatory power for predicting transactions prices over and above the intrinsic value. Market prices reflect a premium for the option to wait to invest that has a mean value of 6% in our sample. We also estimate implied standard deviations for individual commercial property prices ranging from 18 to 28% per year.
  • The validity of environmental benefits transfer: furtherempirical testing, Brouwer, R., & Spaninks, F. A. (1999). Environmental and resource economics,14(1), 95-117. This paper provides further empirical evidence of the validity of environmental benefits transfer based on CV studies by expanding the analysis to include control factors which have not been accounted for in previous studies. These factors refer to differences in respondent attitudes. It goes on to show that the equality of coefficient estimates is a necessary, but insufficient condition for valid benefit function transfer and discusses the implications for previous and future validity testing.
  • A call for soundempirical testingand evaluation of criteria for complicated grief proposed for DSM-V, Prigerson, H. G., & MaCiejewski, P. K. (2006). Omega-Journal of Death and Dying,52(1), 9-19. This paper proposes the need for the empircal testing of a sound CG diagnotics critera.
  • Theory andempirical testingof asset pricing models, Ferson, W. E. (1995). Handbooks in operations research and management science,9, 145-200. This chapter reviews the main asset-pricing theories in finance and discusses combining the models by using a simple, unifying framework. This chapter focuses on models in which expected returns and measures of risk are conditioned on, and may vary with economic information.
  • What is gained and lost when using evaluation methods other thanempirical testing, Desurvire, H. W., Kondziela, J. M., & Atwood, M. E. (1992). People and computers, 89-89. This paper highlights the advantages and disadvantages of using other evaluation models other than empirical testing in solving a problem. This study focuses more on the Heuristic technqiue and how it compares to empirical testing.
  • Faster, cheaper!! Are usability inspection methods as effective asempirical testing?, Desurvire, H. W. (1994).
  • Modifying delusions: The role ofempirical testing, Chadwick, P. D., Lowe, C. F., Horne, P. J., & Higson, P. J. (1994). Behavior Therapy,25(1), 35-49. This study explores the impact of reality testing on beliefs. In this study, the authors first subjected delusions to a period of reality testing, and followed this with a period of conventional verbal challenge. Four people with long term delusions took part in a multiple-baseline across-subjects design. Results show that reality testing was a rather weak method of testing beliefs as it provided ineffective or insubstantial effects. More conclusions are shown in the text.
  • Evaluating the quality of information models:empirical testingof a conceptual model quality framework, Moody, D. L., Sindre, G., Brasethvik, T., & Slvberg, A. (2003, May). InProceedings of the 25th international conference on software engineering(pp. 295-305). IEEE Computer Society. This paper conducts an empirical analysis of a semiotics-based quality framework for quality assuring information models. 192 participants were trained in the concepts of the quality framework, and used it to evaluate models represented in an extended Entity Relationship (ER) language.
  • Empirical testingof auction theory, Hansen, R. G. (1985). The American Economic Review,75(2), 156-159.

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