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SPSS IBMSPSSMPRO Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Modeling | 20% | - Auto-modeling and ensemble techniques - Association and sequence models - Classification and regression models - Clustering and segmentation models |
| Topic 2: Data Preparation | 20% | - Filtering, aggregation and refinement - Sampling, partitioning and balancing - Data transformation and cleaning - Data integration, merging and appending |
| Topic 3: Business Understanding and Planning | 10% | - Align business objectives to data mining goals - CRISP-DM methodology |
| Topic 4: Deployment | 10% | - Scoring new data - Reporting and documentation - Stream export and integration |
| Topic 5: Evaluation and Analysis | 15% | - Validation methods - Interpretation and visualization of results - Model performance assessment |
| Topic 6: Data Understanding | 15% | - Identify data quality issues - Explore and visualize data |
| Topic 7: SPSS Modeler Professional Functionality | 10% | - Scripting and automation - Node palettes and SuperNodes - Stream creation and management |
SPSS IBM SPSS Modeler Professional Certification Sample Questions:
1. Which key items must be identified before a data mining project is started? (Select all that apply)
A) Available data
B) Data quality problem
C) A business problem or question
D) Available expertise on the data and business
2. Summary statistics, such as mean, minimum, maximum, and standard deviation, are available in which of following nodes? (Select all that apply)
A) Data Audit node
B) Sample node
C) Statistics node
D) Table node
3. Which nodes can be used to replace missing data with valid values? [Select all that apply.)
A) Data Audit node
B) Filler node
C) Filter node
D) Distribution node
4. Which nodes are best suited for revealing relationship between categorical (nominal, ordinal) fields? (Select all that apply)
A) Distribution node
B) Table node
C) Matrix node
D) Means node
5. In Sequence modeling, specifying that IDs are contiguous has which effect?
A) Speeds up the processing.
B) Improves the model Silhouette measure.
C) Requires fewer fields to create the model
D) Requires fewer observations to create a valid model.
Solutions:
| Question # 1 Answer: B,C | Question # 2 Answer: A,B,C,D | Question # 3 Answer: A,B,C | Question # 4 Answer: A,D | Question # 5 Answer: A |



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