DIFFICULTIES AND SOLUTIONS IN FINDING THE APPROPRIATE STATISTICAL TECHNIQUE IN RESEARCH

Year 2026, Volume: 16 Issue: 1, 162 - 194, 31.01.2026

Ergul Demir , Metehan Güngör

https://doi.org/10.24315/tred.1575017

Abstract

This study aims at evaluating the opinions of the faculty members and the researchers about the difficulties on the process of data analysis and specifically finding the appriopriate statistical techniques in research. Within the context of qualitative approach, the study gathers opinions through interview forms developed by the researchers and conducts face-to-face and group interviews to obtain in-depth information. There are two study groups in the study. One consists of 61 master or doctoral students selected through criterion sampling. The other comprises 30 faculty members from various public and private universities in Türkiye. The findings indicate that researchers' inadequacies in statistics/mathematics particularly challenge them in data analysis. The lack of knowledge and skills regarding statistics and statistical techniques is identified as a significant obstacle in determining the appropriate statistical technique. To overcome these challenges, researchers often turn to printed and electronic sources, web based platforms and social media, and consult with trusted experts. Faculty members observe that students and other researchers face difficulties in finding the appropriate statistical technique and mastering the algorithms of statistical techniques. Faculty members generally assess researchers' competence in determining the appropriate statistical technique as low to moderate.

Keywords

data analysis , statistical competency , methodological competency , hypothesis test

Project Number

TÜBİTAK 223K382

ARAŞTIRMALARDA UYGUN İSTATİSTİKSEL TEKNİĞİN BELİRLENMESİNDE KARŞILAŞILAN GÜÇLÜKLER VE ÇÖZÜM ÖNERİLERİ

Abstract

Bu çalışmada, veri analizi süreçleri ve özellikle uygun istatistiksel tekniğin belirlenmesinde araştırmacıların yaşadığı güçlükler, başvurdukları çözümler ve öğretim üyelerinin bu konudaki görüşlerinin derinlemesine değerlendirilmesi amaçlanmıştır. Nitel yaklaşımla yürütülen bu çalışmada, araştırmacılar tarafından geliştirilen görüş formları aracılığı ile görüşler alınmış, ayrıca yüzyüze ve grupla görüşmeler gerçekleştirilmiştir. Araştırmanın iki çalışma grubu bulunmaktadır. Bunlardan biri ölçüt dayanaklı örnekleme ile belirlenen 61 lisansüstü öğrencisinden oluşmaktadır. Diğeri Türkiye’deki farklı devlet ve vakıf üniversitelerinde görev yapmakta olan 30 öğretim üyesinden oluşmaktadır. Araştırmanın bulguları, araştırmacıların istatistik/matematik konusundaki yetersizliğinin özellikle veri analizinde araştırmacıları zorladığına işaret etmektedir. İstatistik ve istatistiksel tekniklere yönelik bilgi ve beceri eksikliğinin, uygun istatistiksel tekniği belirlemede aşılması gereken önemli bir güçlük olduğu görülmektedir. Araştırmacıların bu noktada yaşadıkları güçlükleri aşmada, basılı kaynaklardan ve sosyal medya dâhil olmak üzere elektronik kaynaklardan yararlanma ve yetkinliğine güvenilen kişilere danışma çözümlerine başvurduğu görülmektedir. Öğretim üyeleri, özellikle öğrencilerinin ve diğer araştırmacıların uygun istatistiksel tekniği belirlemede ve istatistiksel tekniklerin algoritmalarına hâkim olmada sorunlar yaşadığını gözlemlemektedir. Araştırmacıların uygun istatistiksel tekniği belirlemedeki yetkinliklerini genel olarak düşük ve orta düzeyde değerlendiren öğretim üyeleri bu yetkinlik sorununu, öğrencilerin ve araştırmacıların temel bilgilerin ötesine geçememelerine bağlamaktadır.

Keywords

veri analizi , istatistik yetkinliği , yöntembilim yetkinliği , hipotez testi

Ethical Statement

Yapılan bu çalışmada araştırma etiği ilkeleri gözetilmiş olup gerekli etik kurul izinleri alınmıştır. Bu çalışma TÜBİTAK tarafından desteklenen 223K382 numaralı proje kapsamında yürütülmüş olup, proje, Ankara Üniversitesi Etik Kurulu’nun 24.01.2024 tarihli ve 01 sayılı toplantısında alınan 13 numaralı kararla etik açıdan uygun görülmüştür.

Supporting Institution

TÜBİTAK

Project Number

TÜBİTAK 223K382

References

• Aiken, L. S., West, S. G., Sechrest, L., Reno, R. R., Roediger, H. L. III, Scarr, S., Kazdin, A. E., & Sherman, S. J. (1990). Graduate training in statistics, methodology, and measurement in psychology: A survey of PhD programs in North America. American Psychologist, 45(6), 721-734. https://doi.org/10.1037/0003-066X.45.6.721
• Allam, R. M., Noaman, M. K., Moneer, M. M., & Elattar, I. A. (2017). Assessment of statistical methodologies and pitfalls of dissertations carried out at National Cancer Institute, Cairo University. Asian Pac J Cancer Prev., 18(1), 231-237. Doi:10.22034/APJCP.2017.18.1.231
• Ben-Zvi, D. (2000). Toward understanding the role of technological tools in statistical learning. Mathematical Thinking and Learning, 2(1-2), 127-155. Doi:10.1207/S15327833MTL0202_6
• Ben-Zvi, D., & Garfield, J. (2004). The challenge of developing statistical literacy, reasoning, and thinking. Kluwer Academic Publishers. Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27-40. Doi:10.3316/QRJ0902027
• Budé, L., van de Wiel, M. W. J., Imbos, T., & Berger, M. P. F. (2011). The effect of directive tutor guidance on students' conceptual understanding of statistics in problem-based learning. British Journal of Educational Psychology, 81(2), 309-324. Doi:10.1348/000709910X513933
• Castro Sotos, A. E., Vanhoof, S., Van den Noortgate, W., & Onghena, P. (2007). Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education. Educational Research Review, 2(2), 98-113. Doi:10.1016/j.edurev.2007.04.001
• Cramer, D. (2003). Advanced quantitative data analysis. Open University Press, Mc-Graw Hill.
• Demb, A., & Funk, K. (1999). What do they master? Perceived benefits of the master's thesis experience. NACADA Journal, 19(2), 18-27. Doi:10.12930/0271-9517-19.2.18
• Disman, Ali, M., & Barliana, S. M. (2017). The use of quantitative research method and statistical data analysis in dissertation: An evaluation study. International Journal of Education, 10(1), 46-52. Doi:10.17509/ije.v10i1.5566
• Dowdy, S., Wearden, S., & Chilko, D. (2004). Statistics for research (3rd Ed.). Wiley.
• Fernandez, G. C. J., & Liu, L. (1999). A technology-based teaching model that stimulates statistics learning. Computers in the Schools, 16(1), 173-191. Doi:10.1300/J025v16n01_02
• Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th Ed.). Mc-Graw Hill. Gardenier, J., & Resnik, D. (2002). The misuse of statistics: Concepts, tools, and a research agenda. Accountability in Research, 9(2), 65-74. Doi:10.1080/08989620212968
• Good, P. I., & Hardin, J. W. (2003). Common errors in statistics. John Wiley & Sons.
• Govil, P., Qasem, M. A. N., & Gupta, S. (2015). Evaluation of statistical methods used in ph.d. theses of social sciences in Indian universities. International Journal of Recent Scientific Research, 6(3), 2926-2931. https://api.semanticscholar.org/CorpusID:146262114
• Medaille, A., Beisler, M., Tokarz, R., & Bucy, R. (2022). The role of self-efficacy in the thesis-writing experiences of undergraduate honors students. Teaching & Learning Inquiry, 10, 1-22. Doi:10.20343/teachlearninqu.10.2
• Mizany, M., Khabiri, M., & Sajadi, S. N. (2012). A study of the capabilities of graduate students in writing thesis and the advising quality of faculty members to pursue the thesis. Procedia – Social and Behavioral Sciences, 31, 5-9. Doi:10.1016/j.sbspro.2011.12.006
• Ord, A. S., Ripley, J. S., Hook, J., & Erspamer, T. (2016). Teaching statistics in APA-accredited doctoral programs in clinical and counseling psychology: A syllabi review. Teaching of Psychology, 43(3), 221-226. Doi:10.1177/0098628316649478
• Pallant, J. (2010). SPSS survival manual: A step by step guide to data analysis using SPSS (4th edition). Open University Press, McGraw-Hill Education.
• Qasem, M. A. N., Govil, P., & Gupta, S. (2015). A comparative study of the levels of statistical competency among post-graduate students of the universities of Yemen and India. Open Journal of Social Sciences, 3, 130-137. Doi:10.4236/jss.2015.32017
• Pratt, D., Davies, N., Connor, D. (2011). The role of technology in teaching and learning statistics. In Batanero, C., Burrill, G., Reading, C. (Eds.), Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education. New ICMI Study Series, Vol 14. Springer. Doi:10.1007/978-94-007-1131-0_13
• Resnik, D. B. (2000). Statistics, ethics, and research: An agenda for education and reform. Accountability in Research, 8(1-2), 163-188. Doi:10.1080/08989620008573971
• Sprent, P. (2003). Statistics in medical research. Swiss Med Wkly, 133(39-40), 522-529. https://doi.org/10.4414/smw.2003.10470
• Vogt, W. P., & Johnson, R. B. (2011). Dictionary of statistics & methodology (4th Ed.). SAGE. Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P. M., & Berger, M. P. F. (2013). The effect of guidance in problem-based learning of statistics. The Journal of Experimental Education, 82(3), 391-407. Doi:10.1080/00220973.2013.813365
• Lie, R., Abdullah, C., He, W., & Tour, E. (2016). Perceived challenges in primary literature in a master’s class: Effects of experience and instruction. CBE—Life Sciences Education, 15(4), 1-12. Doi:10.1187/cbe.15-09-0198
• Nasser, F. (2004). Structural model of the effects of cognitive and affective factors on the achievement of Arabic-speaking pre-service teachers in introductory statistics. Journal of Statistics Education, 12(1). 1-19. Doi:10.1080/10691898.2004.11910717
• Round, J. E., & Campbell, A. M. (2013). Figure facts: encouraging undergraduates to take a data-centered approach to reading primary literature. CBE—Life Sciences Education, 12(1), 39-46. Doi:10.1187/cbe.11-07-0057
• Syarief, N. H., Aba, M. M., & Zulfikar, R. N. (2023). Analysis of the statistical literacy ability of sociology education students. Edumatica: Jurnal
• Pendidikan Matematika, 13(03), 203-213. Doi:10.22437/edumatica.v13i03.28530
• Yusof, I. J., Latif, A. A., & Supie, H. S. (2021). Assessing statistical literacy level of postgraduate education research students in Malaysian research universities. Turkish Journal of Computer and Mathematics Education, 12(5), 1318-1324.
• Zhang, P., & Han, C. (2023). Examining statistical literacy, attitudes toward statistics, and statistics self-efficacy among applied linguistics research students in China. International Journal of Applied Linguistics, 1-17. Doi:10.1111/ijal.12500