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Statistical Fallacy: a Menace to the Field of Science

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Statistical Fallacy: a Menace to the Field of Science International Journal of Scientific and Research Publications, Volume 9, Issue 6, June 2019 297 ISSN 2250-3153 Statistical Fallacy: A Menace to the Field of Science Kalu Emmanuel Ogbonnaya*, Benard Chibuike Okechi**, Benedict Chimezie Nwankwo*** * Department of Ind. Maths and Applied Statistics, Ebonyi State University, Abakaliki ** Department of Psychology, University of Nigeria, Nsukka. *** Department of Psychology and Sociological Studies, Ebonyi State University, Abakaliki DOI: 10.29322/IJSRP.9.06.2019.p9048 http://dx.doi.org/10.29322/IJSRP.9.06.2019.p9048 Abstract- Statistical fallacy has been a menace in the field of easier to understand but when used in a fallacious approach can sciences. This is mostly contributed by the misconception of trick the casual observer into believing something other than analysts and thereby led to the distrust in statistics. This research what the data shows. In some cases, statistical fallacy may be investigated the conception of students from selected accidental or unintentional. In others, it is purposeful and for the departments on statistical concepts as it relates statistical fallacy. benefits of the analyst. Students in Statistics, Economics, Psychology, and The fallacies committed intentionally refer to abuse of Banking/Finance department were randomly sampled with a statistics and the fallacy committed unintentionally refers to sample size of 36, 43, 41 and 38 respectively. A Statistical test misuse of statistics. A misuse occurs when the data or the results was conducted to obtain their conception score about statistical of analysis are unintentionally misinterpreted due to lack of concepts. A null hypothesis which states that there will be no comprehension. The fault cannot be ascribed to statistics; it lies significant difference between the students’ conception of with the user (Indrayan, 2007). Some of the basic tenets of statistical concepts with respect to their departments was tested statistics are often misunderstood and in some cases, deliberately using One-way Analysis of Variance (ANOVA). The hypothesis misused to lend weight to false assertions (Salter, 2012). was rejected based on F(3,157) = 23.471 and p-value < 0.001 Statistical fallacies occur when an argument’s conclusion is not which suggests statistical significant difference in their supported by the numerical evidence provided as premises conceptions. It was then found out that Statistics students have a (Klass, 2008). higher understanding about statistical concepts followed by Statistics, which has over the years embedded into most Economics, Psychology and Banking/Finance students with a fields of study due to its need in research works, has become a low understanding of Statistical concepts using a post-hoc discipline of interest. Practitioners and professionals in the fields (Tukey HSD) test and mean chart. of study where statistics is needed have delved into statistical analysis in other to remain independent. Due to the inaccurate Index Terms- Statistics, Fallacy, Menace, Sciences, Misuse, analysis of data, the world of research has not been without Misconception, fallacies, statistical methods. fallacious assertions. Analysts wrongly interpret statistical data which may be out of their selfish interest to prove a false assertion. In media, Journalists sometimes sell their news through I. INTRODUCTION wrong statistical captions and analysis of a published data. In he science of statistics is broadly divided into descriptive politics, analysts misinterpret statistical data in other to win the T and inferential statistics. In research study, statistics is mind of the people on certain issues of interest or to make the needed from the beginning to the end of the study. Statistics is government consent to an idea or forecast because it can be the systematic collection and analysis of numerical data, which statistically proven. enables the researcher to investigate relationships among This research borders on the misuse of statistics by phenomena and develop accurate and reasonable inference students which is caused by inappropriate understanding of (McGraw−Taylor, 2007; Annapurna, 2017). The use of statistics statistics, thereby leading to statistical fallacy. Nevertheless, in almost all the fields of study can never be over emphasized. statistical fallacy cannot be explained or written about without Since statistics deals with data collection and data analysis which taking cognizance to misconceptions of statistical concepts. is mostly used in making inference, extreme carefulness needs to Statistical misuse can also be as a result of the misconceptions of be applied when working with data because, the usefulness of its methods and techniques by students and analysts. A solid data in any field of study depends greatly on the method of understanding of inferential statistics is of major importance for collection, analysis and interpretation. The conclusion drawn will designing and interpreting empirical results in any scientific be accurate if the data collection processes and the statistical discipline (Sotos, 2007). methods were carefully and judiciously applied. Inappropriate Kirk (2001) explained that inferential ideas seem to be use of these processes and methods will obviously lead to especially sensitive to be misunderstood and students are often inaccurate and fallacious conclusions. prone to fall into deep misconceptions. This is because they Statistical fallacy refers to the wrong interpretation of data require students to understand and connect many abstract which may arise in the collection, presentation, analysis and concepts such as sampling distribution and significance level. interpretation of data. Statistics are supposed to make analysis Statistical misconceptions are argued to hinder meaningful http://dx.doi.org/10.29322/IJSRP.9.06.2019.p9048 www.ijsrp.org International Journal of Scientific and Research Publications, Volume 9, Issue 6, June 2019 298 ISSN 2250-3153 learning, impede research progress and interfere with decision (i.e. Get the learner to believe in his or her personal abilities to making. For students, such misconceptions may be generated by correctly complete a behavior). Behavioural determinant looks at poor understanding reinforced by statements uttered or written by the response an individual receives after they perform a behavior one’s mentor or teacher (Huck, 2009). When these (i.e. Provide chances for the learner to experience successful misconceptions are applied in research studies, the results of the learning as a result of performing the behavior correctly). analysis become fallacious. The use of the inappropriate Environmental determinant is the aspects of the environment or statistical methods, techniques and the analysis cost time and setting that influence the individual's ability to successfully lost, it gives harm to science and humanity. Even if the study is complete a behavior (i.e. Make environmental conditions carefully planned to be conducted as a result of applications with conducive for improved self-efficacy by providing appropriate errors, the misleading results might be obtained, and mislead support and materials). others who will reference the study (Ercan, 2007). Cognition is usually defined as the mental processes, Fear and wrong orientation has contributed to students’ representations, and activities involved in the acquisition and use misconception about statistical concepts. The course lecturers in of knowledge. Statistical cognition is accordingly defined as the the undergraduate level have in most cases failed to properly processes, representations, and activities involved in acquiring mentor the students. John and David (2002) added that for one to and using statistical knowledge (Beyth-Marom, Fidler & apply any statistical method correctly, one must have information Cumming, 2008). The issues relevant in the study of statistical about the variables used, information about the sampling process cognition can be explained in three aspects. One aspect is how used and a sound understanding of the theory and assumptions people acquire and use statistical knowledge and how they think underlying the method. If a researcher does not use a method about statistical concepts, this is the descriptive facet of statistical correctly, then conclusions may overestimate or underestimate an cognition. The study of how people should think about statistical important relationship or effect. concepts is the normative, also an important aspect of statistical When statistical fallacies are observed especially by non- cognition as this is often what we are exposed to (e.g., in school) scientists, it leads to the distrust in statistics where people will and it is also the standard to which our performance is usually choose not to accept statistical inference, causing a menace to the compared. Finally, the question of closing the gap between the field of sciences. Statistical fallacy is undoubtedly a very great descriptive (the “is”) and the normative (the “should”) is the menace in the field of sciences. Lack of appropriate training, prescriptive which is a critical issue in statistical cognition. As inadequate orientation, misunderstanding and misconceptions has such, statistical cognition is a field of theory research and contributed a great deal in fallacious interpretation and data application concerned with normative, descriptive, and analysis. Since Aristotle’s time, the generally accepted method of prescriptive aspects. It focuses on (a) developing and
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