Hi

Several examples with interpretation is given in:

1. Landau, S. and Everitt, B. S.(2004). A Handbook of Statistical analyses using SPSS.

2.Howitt, D. and Cramer, D.(2008). Introduction to SPSS.

Regards,

Zuhair

Hello Karolina,

If I understand your question correctly:

1. If all independent variables (IVs) were uncorrelated with each other, then part/partial correlation with the dependent variable (DV) will not differ from zero-order (ordinary, bivariate) correlation of each IV with DV.

2. Thus, if there is a discrepancy between the two, it is because of redundancy (multicollinearity) among the IVs. Excessive collinearity can cause other technical issues as well, including biased estimates of the regression coefficients.

A famous citation that discusses a small data set with huge multicollinearity (in an attempt to determine how satisfactorily software packages of the time were able to cope with same) is:

Longley, J. W. (1967). An appraisal of least squares programs from the point of the user. Journal of the American Statistical Association, 62, 819-841. doi:10.2307/2283673

Good luck with your work!

Hi

Please refer to chapter 4, pages 89-125 of the attached book.

Regards,

Zuhair

Beside the resources recommended by Dr. Al-Hemyari, you might also find this quite useful:

SPSS Instruction Manual

https://www.westga.edu/academics/research/vrc/assets/docs/spss_basics.pdf