Mention the underpinning or a synopsis of the structure being measured during the experiment. The introduction must talk about past critiques and techniques and how this analysis differs from past experiments.
Talk about the results of the analysis after the introduction. Explain the factor analysis extraction method used and why that particular method was used. The methods are: principal components (PC) and principle axis factoring (PAF). The PAF analyzes only the variance in the items that is shared, while the PC analyzes all of the variances in all of the items. For example, you would use a principal component if there are many components that make up the experiment.
Talk about the process used for deciding how many factors or items were selected. In addition, you must explain which factors and items you have deleted from the past experiments and why these factors were deleted from the new experiment.
Define terms you use and bring description to concepts that are uncommon to a regular person. In addition to clarifying your factors, you must create meaningful names or phrases for each factor. One way to name your factor is to think back about the techniques used in the factor and taking two or three important terms from that technique.
Use a detailed table to display the data you have acquired through the experiments. Each row should introduce a new, important component from the PAF or PC method, while the columns should address the different factors.
Rethink and use a check list to see if all of the components of the factor analysis are complete. The analysis must have clear, well-defined terms. Make sure all of the important factors are presented in the analysis and that there is a relevance factor. In addition, you should mention how one would test the experiment even further. If you want, you should allow a professor or another student to make sure everything is present.