Factor analysis of Likert scale: Analysis and Interpretation using SPSS скачать в хорошем качестве

Factor analysis of Likert scale: Analysis and Interpretation using SPSS

This tutorial explains how to perform and interpret exploratory factor analysis (EFA) on Likert scale in SPSS. I discuss how to enter the data, select the various options, interpret the output (e.g., communalities, eigenvalues, factor loadings). I also discuss the difference among extraction techniques (Principal components analysis or PCA, Principal Axis Factoring or PAF and Maximum Likelihood or ML). I also discuss the difference between orthogonal and oblique rotation techniques like Varimax and Promax within SPSS. Likert scale is a commonly used rating scale in surveys, typically containing several statements, and respondents rate their level of agreement or disagreement on a scale ranging from strongly disagree coded as 1 to strongly agree coded as 5. ------------------------------------------------------------------ ✅ Download EFA and CFA guidelines and dataset: https://redev.gumroad.com/l/EFAandCFA... ✅ Quantitative data analysis one-on-one consultation service: https://drbenhima.com/quantitative-da... ---------------------------------------------------------------------- 📌 Mohamed Benhima, PhD WhatsApp: +212619398603 / wa.link/l6jvny LinkedIn:   / mohamed-benhima-phd-6a1087109   Mohammed V University, Rabat, Morocco ( [email protected] ) Sorbonne University, Paris, France ( [email protected] )