The Art of Data Science(Chapter7. Formal Modeling)

Produced by Lee Tae Young

Formal Modeling

Formal Modeling

Setting expectations.

Collecting Information.

Revising expectations.

Primary model Secondary models

Associational AnalysesOutcome. Key predictor. Potential confounders.

EX) Online advertising campaignExpectationsSetting Expectations.More realistic dataEvaluation

1. Effect size.2. Plausibility. (타당성 )3. Parsimony. (간결 )

Prediction Analysesclassification problem

Expectations

Real world data

Evaluation1. Prediction quality.2. Model tuning.

3. Availability of Other Data.

Summary• Formal Modeling : 분석의 기본 Frame 제공– 기본 : 엄격함 , 시험하기 위한 도구

• Prediction 의 근간이 됨

Communication

Routine communication

The Audience(대상 )

Content(내용 )Style

Attitude