Using Factor Analysis to Extract The Most Important Factors Influencing The Economic Activity of large Industrial Establishments in Iraq in 2020

الملخص

             Principal Component Analysis (PCA) is one of the most important statistical methods in factor analysis. It is used to reduce data dimensions and extract the underlying factors that represent the underlying structure of variables. This research aims to study the effectiveness of the principal components approach in anal  yzing data from a sample of (719) large industrial establishments in Iraq in 2020, using the JASP program .The study relied on a set of basic steps applied to principal components analysis, which included (data preparation and normalization, calculating the variance-covariance matrix, extracting the principal components using singular value decomposition (SVD), and interpreting the extracted factors in light of the explained variance).

The results showed that the principal components analysis method clearly contributed to simplifying the data structure by reducing the number of input variables while retaining most of the total variance, allowing for a clearer and more accurate interpretation of the factors influencing the performance of large industrial establishments. This approach also helped uncover common patterns among variables and obtain a more comprehensive picture of the economic data under study.