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SPSS IBMSPSSMBPDM Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Preparation30%- General operations in SPSS Modeler
- Sampling, aggregating and cleaning data
- Automated data preparation
- Combining and restructuring data
- Deriving and reclassifying variables
Topic 2: Business Understanding15%
Topic 3: Evaluation and Deployment15%- Interpreting and exporting results
- Model assessment
Topic 4: Data Understanding20%
Topic 5: Modeling20%- CRISP-DM methodology
- Applying data mining techniques

SPSS IBM SPSS Modeler - Business Partner Data Mining Associate Sample Questions:

1. To correctly read the Excel@ file shown below,

which dialog box settings are appropriate?

A) B)


D)

A) Exhibit A
B) Exhibit C
C) Exhibit D
D) Exhibit B


2. Which node can be used to impute (estimate) missing values?

A) Data Audit node
B) Filler node
C) Reclassify node
D) Balance node


3. True or false: the CRISP-DM Process Methodology is a linear process.

A) False
B) True


Solutions:

Question # 1
Answer: C
Question # 2
Answer: A
Question # 3
Answer: A

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