Data preprocessing is the vital and fundamental step that must be taken prior further data analysis. Since the heath of the decision which is taken after the analysis of the data largely depends on the collected data, that is how well the data is being collected and prepared for further analysis.
In the descriptive analysis, from the b column to g column is taken into consideration, where the most of the histograms were slightly left skewed, however, most of them were having only one high peak, which can be taken into consideration.In terms of the outlier,most of the outlier (hollow) is seen from column c to g. The dataset , N=625 samples is observed with mean mostly 4.7 along with the standard deviation with one standard deviation that is 0.9 to 1.07.
Here we have performed the Principal component analysis, in PCA and factor analysis, exploratory data analysis can be achieved since it is used for generation of the theory also can be defined as a bottom up approach.It is a process to identify the smaller number of dimensions. The goal of PCA and factor analysis accounts for the variance in the pearson correlation matrix which further hold extraction and rotation.
assignment -2 output and using Bartlett Scores
specify/propose a factor structure (simple mediation or simple moderation) and estimate it using path analysis (using process tool or Amos or Any other tool) technique or structural equation modelling to test specific hypothesis.
Data Centric 