SPSS IBMSPSSMPRO : IBM SPSS Modeler Professional Certification

IBMSPSSMPRO real exams

Exam Code: IBMSPSSMPRO

Exam Name: IBM SPSS Modeler Professional Certification

Updated: Aug 07, 2026

Q & A: 73 Questions and Answers

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SPSS IBMSPSSMPRO Exam Syllabus Topics:

SectionWeightObjectives
Data Understanding15%- Explore and visualize data
- Identify data quality issues
Evaluation and Analysis15%- Validation methods
- Interpretation and visualization of results
- Model performance assessment
Modeling20%- Clustering and segmentation models
- Association and sequence models
- Classification and regression models
- Auto-modeling and ensemble techniques
Deployment10%- Scoring new data
- Reporting and documentation
- Stream export and integration
Business Understanding and Planning10%- Align business objectives to data mining goals
- CRISP-DM methodology
Data Preparation20%- Sampling, partitioning and balancing
- Data transformation and cleaning
- Data integration, merging and appending
- Filtering, aggregation and refinement
SPSS Modeler Professional Functionality10%- Node palettes and SuperNodes
- Scripting and automation
- Stream creation and management

SPSS IBM SPSS Modeler Professional Certification Sample Questions:

1. To score new data using an existing model, the user must:

A) Not change the data source and develop a new model for that data.
B) Change the data source and rename the fields so they do not match the names of the fields in original file.
C) Change the data source and develop a new model for that data.
D) Change the data source and rename the fields as needed to match the names of the in original file.


2. Which Source node would you use to read text from a free field (delimited) text file?

A) Fixed File node
B) Data Collection node
C) Var. File node
D) Enterprise View node


3. The set Random seed option on the sample node is required if you want to draw the same random sample with the same records more than once.

A) True
B) False


4. Consider the output from the analysis node.

For the training data set, the Neutral Net and the C5 model make the same prediction:

A) 87.79% of the time.
B) 92.77% of the time
C) 87.62% of the time
D) 93.80% of the time


5. Which statements are true of the Feature Selection node? (Select all that apply)

A) The Input fields can only be continuous measurement.
B) The Target fields can be either categorical or continuous measurement.
C) Input fields can be selected on the basis or importance.
D) When a target field is not specified then it will create a generalized output.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: C
Question # 3
Answer: A
Question # 4
Answer: C
Question # 5
Answer: B,C

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