I am doing e research about soft skills vs technical competence in an associate auditors career. this research also focus on career advancement. my conceptual model, i have soft skill and technical competence as independent variable and career advancement as dependent variable.
To make the analysis which analysis is better, Pearson or regression?
Thanks in advance
You can use both, assuming that your independent and dependent variables are in interval scale. You can use Pearson correlation to determine the relationships of variables. If you will find using correlation coefficients that your independent and dependent variables are related. You can use regression to build a prediction model of career advancement considering soft skill and technical competence.
Multiple regression analysis will give better results for your study.
Y = career advancement
X1 = soft skills
X2 = technical competence
Multiple regression in a form of Y = a +b1x1 +b2x2 + error may be used. For statistical test, Ftest ANOVA may be used: F = msr / mse.
If your dependent variable is categorical, you can use logit or probit regression and chi square test.
Additionally, others have mentioned about Ftest Anova, Pearson Correlation test.
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