I thought all was well, what do I get back...the following recommended changes came from my adviser:
1. Pearson correlations used to determine the strength and significance of the linear association between the independent variables and the dependent variables.
2. Multiple linear regression analyses used to determine if there was a significant relationship between the independent variables and the dependent.
3. Parameter estimates computed and analyzed for testing of research questions and hypothesis.
4. The bivariate association between the career efficacy and the independent variables measured by the AMAQ subscales assessed using Pearson correlation coefficient if the data are normally distributed.
5. Spearman correlation used for the subscales that are semi-continuous (or ordinal).
6. Statistical significance of the bivariate correlations assessed.
7. Association explored further in linear regression analysis for significant AMAQ subscales to adjust for participants demographic characteristics such as age, gender, rank, area of concentration and educational attainment etc.
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