A COMPARATIVE ANALYSIS OF SPEARMAN AND PEARSON CORRELATION USING SPSS
Abstract
Correlation is one of the statistical methods used to measure the relationship between two variables. Two commonly used types of correlation are Spearman Correlation and Pearson Correlation. Spearman Correlation is used for ordinal data or data that do not meet the assumption of normality, while Pearson Correlation is applied to interval or ratio data that follow a normal distribution. This study aims to compare the results of analyses using these two correlation methods through the SPSS software. By analyzing both simulated and real-world data, tests were conducted on various data scenarios, including variations in data types, distribution patterns, and levels of variable relationships. The results indicate that Pearson Correlation is more sensitive to normally distributed data, whereas Spearman Correlation provides more stable results for non-normally distributed data or data containing outliers. This article also presents a step-by-step guide for using SPSS to perform analyses with both correlation methods, making it easier for readers, especially students and researchers, to apply the appropriate method based on their data characteristics. By understanding the differences and advantages of each method, users are expected to choose the right approach for correlation analysis.
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Armstrong, R. A. (2019). Should pearson's correlation coefficient be avoided?. Ophthalmic and Physiological Optics, 39(5), 316-327.
Benesty, J., Chen, J., and Huang, Y. (2008). On the importance of the pearson correlation coefficient in noise reduction. IEEE Transactions on Audio, Speech, and Language Processing, 16(4), 757-765.
Blackwell, D., Leaman, C., Tramposch, R., Osborne, C., and Liss, M. (2017). Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences, 116, 69-72.
Chok, N. S. (2010). Pearson's versus spearman's and kendall's correlation coefficients for continuous data. Doctoral dissertation, University of Pittsburgh.
Dancey, C. P., and Reidy, J. (2017). Statistics without maths for psychology (7th ed.). Pearson Education.
De Winter, Joost C. F.,Gosling, Samuel D.,Potter, Jeff. (2016). Comparing the pearson and spearman correlation coefficients across distributions and sample sizes: a tutorial using simulations and empirical data. Psychological Methods, 21(3), 273-290
El Hasbi, A. Z., Damayanti, R., Hermina, D., and Mizani, H. (2023). Penelitian korelasional (metodologi penelitian pendidikan). Al-Furqan: Jurnal Agama, Sosial, dan Budaya, 2(6), 784-808.
Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. London: SAGE Publications.
Gauthier, J. G. (2001). Understanding spearman's and pearson's correlation coefficients. Journal of Statistics Education.
Gilpin, A. R. (1993). Table for conversion of kendall's tau to spearman's rho within the context of measures of magnitude of effect for meta-analysis. Educational and psychological measurement, 53(1), 87-92.
Hart, C. (1998). Doing a Literature Review: Releasing the Social Science Research Imagination. London: Sage Publications.
Hauke J., Kossowski T., (2011). Comparison of values of Pearson’s and Spearman’s correlation coefficient on the same sets of data. Quaestiones Geographicae 30(2), Bogucki Wydawnictwo Naukowe, Poznań, pp. 87–93.
Hinkle, D. E., Wiersma, W., and Jurs, S. G. (2003). Applied Statistics for the Behavioral Sciences. Boston: Houghton Mifflin.
Khotimah, K. (2017). Analisis Korelasi Rank Kendall dan Aplikasinya dengan Program SPSS. Doctoral dissertation, Universitas Negeri Semarang.
Marie-Therese Puth, Markus Neuhauser, Graeme D. Ruxton. (2015). Effective use of spearman's and kendall's correlation coefficients for association between two measured traits. Animal Behaviour 102, 77-84
Mayer, J. D., and Salovey, P. (1997). What is emotional intelligence? In Salovey, P., and Sluyter, D. (Eds.), Emotional Development and Emotional Intelligence: Educational Implications. Basic Books. pp. 3-31.
Mukaka, M. M. (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi Medical Journal, 24(3), 69–71.
Nugroho, S., Akbar, S., and Vusvitasari, R. (2008). Kajian Hubungan Koefisien Korelasi Pearson (r), Spearman-rho (?), Kendall-Tau (?), Gamma (G), dan Somers. Gradien, 4(2), 372-381.
Przybylski, A. K., Murayama, K., DeHaan, C. R., and Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 29(4), 1841-1848.
Ratner, B. (2009). The correlation coefficient: Its values range between +1/−1, or do they? Journal of Targeting, Measurement and Analysis for Marketing, 17(2), 139–142.
Rebekić, A., Lončarić, Z., Petrović, S., and Marić, S. (2015). Pearson's or spearman's correlation coefficient-which one to use?. Poljoprivreda, 21(2), 47-54.
Schmid, F., and Schmidt, R. (2007). Multivariate extensions of spearman's rho and related statistics. Statistics and probability letters, 77(4), 407-416.
Schober, P., Boer, C., and Schwarte, L. A. (2018). Correlation coefficients: appropriate use and interpretation. Anesthesia and Analgesia, 126(5), 1763–1768.
Sedgwick, P. (2012). Pearson’s correlation coefficient. BMJ, 345, e4483.
Siagian, N. (2021). Statistika dasar: konseptualisasi dan aplikasi. Surakarta: Kultura Digital Media.
Sugianto, M., and SmitDev, S. T. (2014). Mengolah data bisnis dengan SPSS 20. Elex Media Komputindo.
Suryono, H., and Rejekiningsih, T. (2007). Uji persyaratan analisis statistik. Jurnal Inovasi Pendidikan, 8(2).
Thirumalai, C., Chandhini, S. A., and Vaishnavi, M. (2017, April). Analysing the concrete compressive strength using pearson and spearman. International conference of electronics, communication and aerospace technology (iCECA), 2, pp. 215-218.
Wulansari, A. D. (2016). Aplikasi statistika parametrik dalam penelitian. Yogyakarta: Pustaka Felicha.
Yolanda, F., Egianto, F., Armita, F., Wahyuni, L. A., Cahyani, R., Rahayu, S., and Saputri, T. (2024). Studi Literatur: Korelasi Bivariat Menggunakan Uji Korelasi Koefisien Kontingensi. Jurnal Pendidikan Tambusai, 8(2).
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