Two Days Workshop on Statistical Analysis and Structural Equation Modeling using IBM-SPSS-Amos 25.0.

Two Days Workshop on Statistical Analysis and Structural Equation Modeling using IBM-SPSS-Amos 25.0.

Brochure overview

Date:  29 & 30 March 2019 (Friday - Saturday)

Time:     9.00 am - 5.00 pm

Venue:    Wisma R & D, University of Malaya

Fee:     RM 400 (UM staff and student)

           RM 450 (non-UM staff and student)

Participant will receive a Certificate of Achievement
Book, materials and refreshments will be provided.

WORKSHOP SINOPSIS: 

This workshop is aimed for academicians, researchers, and postgraduate students who intend to analyse their work using Structural Equation Modelling (SEM). SEM is the second-generation method of multivariate statistical analysis which replace the older method of Ordinary Least Square (OLS) due to some limitations especially when the model is complicated and the latent constructs involve in the study. The analysis using SEM is fast, efficient and accurate where the researchers could convert their theoretical framework into SPSS-Amos graphic, input data, and execute. Through SPSS-Amos software, the researchers could assess their latent construct for validity (construct validity, convergent validity and discriminant validity), reliability, and normality distribution. The facilitator would teach participants through the hands-on approach using real Phd datasets. More importantly, the detailed notes with systematic outline are available in the textbook titled SEM Made Simple written by the facilitator.    

 

OBJECTIVE:

The objectives: the participants will be exposed to thorough and proper research methodology and various types of statistical analysis. As for SEM, the participants will be taught how to convert the research framework to Spss Amos Graphics and execute SEM procedure for analysis. More importantly the procedure for testing direct effect hypothesis, the mediation effects as well as the moderation effects hypotheses will also be explained. The hands on exercises will use real Phd models & datasets.

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