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SPSS IBMSPSSMPRO Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Modeling | 20% | - Association and sequence models - Clustering and segmentation models - Auto-modeling and ensemble techniques - Classification and regression models |
| Topic 2: SPSS Modeler Professional Functionality | 10% | - Node palettes and SuperNodes - Scripting and automation - Stream creation and management |
| Topic 3: Deployment | 10% | - Scoring new data - Reporting and documentation - Stream export and integration |
| Topic 4: Data Understanding | 15% | - Identify data quality issues - Explore and visualize data |
| Topic 5: Data Preparation | 20% | - Data transformation and cleaning - Data integration, merging and appending - Filtering, aggregation and refinement - Sampling, partitioning and balancing |
| Topic 6: Evaluation and Analysis | 15% | - Validation methods - Interpretation and visualization of results - Model performance assessment |
| Topic 7: Business Understanding and Planning | 10% | - CRISP-DM methodology - Align business objectives to data mining goals |
SPSS IBM SPSS Modeler Professional Certification Sample Questions:
Question 1
In Sequence modeling, specifying that IDs are contiguous has which effect?
A. Requires fewer fields to create the model
B. Speeds up the processing.
C. Requires fewer observations to create a valid model.
D. Improves the model Silhouette measure.
Question 2
In two step node shown below, what does standardize numeric fields mean?
A. Eliminate outliers to improve results.
B. Transform the numeric fields to a scale with a mean of zero and variance of one.
C. Use only the numeric fields scale.
D. Limit the number of created clusters.
Question 3
Which Decision Tree method can only work categorical (non-continuous) targets? (Select all that apply)
A. CHAID
B. QUEST
C. C5
D. C & RT
Question 4
Using the Linear node, what are the advantages of creating a standard model without boosting or bagging? (Select all that apply)
A. Higher accuracy
B. None of the above
C. Faster to score
D. Easier interpretation
Question 5
Assume that you have the field A, B, C, and D and you wish to find the sum of values even if there are $null$ missing values in one or more fields.
Which expression would accomplish this task?
A. sum_n( [A, B, C, D])
B. to_real (A)+ to_real (B)+ to_real (C)+ to_real (D)
C. A+B+C+D
D. sum_n(A B C D})
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: B,C | Question 4 Answer: A,C | Question 5 Answer: A |






