Which two palettes in SPSS Modeler contain nodes for data preparation?

The most relevant palettes in SPSS Modeler that contain nodes for data preparation are indeed the Field Ops and Record Ops palettes. These palettes include various nodes that assist in preparing data for analysis, such as filtering, transforming, and merging data sets.

Data preparation is a crucial step in the data mining process, as it ensures that the data is in a suitable format and clean for modeling. The nodes found within the Field Ops palette typically deal with manipulating individual fields, while the Record Ops palette focuses on operations that apply to entire records within the dataset. Both palettes provide the tools necessary to shape and clean data, making them essential for effectively preparing data prior to analysis.

In contrast, the other options do not adequately contain the necessary nodes for data preparation. For instance, the Export and Sources palette would mainly focus on importing data and exporting results rather than preprocessing the data. The Output Ops and Statistics palette deals with outputting results and statistical analysis rather than preparing the data itself. Lastly, while the Sources and Graphs palette provides nodes for data sourcing and visualization, they do not specifically target the preparation of data for analysis. Thus, Field Ops and Record Ops are identified as the correct choices for data preparation in SPSS Modeler.