A process-structure linkage of polyethylene under uniaxial strain is developed by performing analysis of published experimental data sets. The data sets created at Argonne National Lab were made by recording X-ray diffraction plots of polymer samples mounted in a stress-strain testing apparatus where strain was applied continuously to induce structure evolution. A total of 12 unique samples were tested, producing time resolved Small Angle X-ray Scattering (SAXS) and Wide Angle X-ray Scattering (WAXS) image sets and their corresponding applied strain data for each sample. The samples differed in density, thickness, and original manufacturing process. Previous work was done by David Brough and Abhiram Kannan on this dataset to extract correlations using the SAXS data which link the 1-1000nm scale structure features to the strain, thickness, density, and original manufacturing process. The first objective of the current project involves finding process-structure correlations as a function of thickness, density, and original manufacturing process using the WAXS data sets in order to explore the effects of sub-1nm structure features. The 2-point statistics approach typically used to quantify and compare microstructure in a meaningful and unbiased way was found to be unnecessary. The X-ray plots themselves represent physical structure information in inverse space, giving us an unbiased statistical representation of the structure. The WAXS data can then be directly subjected to PCA after which the relevant data is extracted and correlations are sought. This objective is a reasonable goal for the Materials Informatics project and can be expanded on in the future to find SAXS-WAXS correlations. The second objective of this work is to relate the findings of the WAXS dataset analysis to the findings of the previously done SAXS analysis linking the sub-1nm and the 1-1000nm length-scales to give a comprehensive process-structure linkage of polyethylene under uniaxial strain.