Park University Computer Science Question Factor Analysis

1. Pick any relevant to your major dataset that you would like to analyze. Avoid use the same or similar datasets to one you use for your final project or previous assignments. Make sure not to use datasets from an educational literature on regression analysis.
   Note that for successful factor analysis you need to have at least 15 variables, that can potentially have common themes (factors).
   Avoid using any datasets referred in educational or similar literature. Use original datasets, for original studies.
2. Use R, Python or other tool to compute exploratory factor analysis. 
3. Submit a Word report describing each step and a result of this process, include relevant scripts and outputs produced by the tool you use. On top of that your report has to include:
   1. Description of the dataset and the expectation of the factors.
   2. Description of the factors, variable loads.
   3. Explanation of the meaning of the factors.
   4. Give an example how the model can be used to predict the factor scores.
   5. Discuss the model’s quality.
   6. Please do not use Kaggle. Sites like Kaggle are not appropriate as they have an abundance of code/script/solutions available.

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