분석 결정을 내리며 ENA를 배우세요.

초기화

33 개 수업

페이지 4 / 6

해석중급35 분2026년 8월 5일
ENA 아카데미 수업 19

Report ENA Effect Sizes and Intervals

Use the shared synthetic design-talk dataset to practise reporting the magnitude and uncertainty of planned ENA coordinate contrasts alongside plots and p-values, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

effect sizeconfidence intervalcoordinate comparison
튜토리얼 열기
연구 설계중급35 분2026년 8월 6일
ENA 아카데미 수업 20

Plan Multiple-Group ENA Contrasts and Multiplicity

Use the shared synthetic design-talk dataset to practise comparing three or more groups without forcing them into a two-group means rotation or reporting every favorable pairwise difference, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

multiple groupsplanned contrastsmultiplicity
튜토리얼 열기
모델링중급35 분2026년 8월 7일
ENA 아카데미 수업 21

Build Longitudinal ENA Trajectories in One Space

Use the shared synthetic design-talk dataset to practise representing successive network states as ordered paths while keeping every time point co-registered in one analytic space, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

longitudinal trajectoryshared spacetime ordering
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모델링중급35 분2026년 8월 8일
ENA 아카데미 수업 22

Choose Directed or Ordered Network Analysis When Sequence Matters

Use the shared synthetic design-talk dataset to practise deciding whether the research question concerns undirected association, directed ordering, or a stricter transition process, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

ordered network analysisdirected edgessequence
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데이터 준비중급35 분2026년 8월 10일
ENA 아카데미 수업 23

Prepare Multimodal Events for ENA

Use the shared synthetic design-talk dataset to practise aligning speech, action, sensor, screen, or spatial events on a defensible common timeline before modeling cross-modal connections, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

multimodal dataevent alignmentsensor traces
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데이터 준비중급35 분2026년 8월 11일
ENA 아카데미 수업 24

Validate Automated Codes Before They Enter ENA

Use the shared synthetic design-talk dataset to practise evaluating whether model-generated labels are accurate enough for relational analysis and how classification errors propagate into edges, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

검토된 튜토리얼 본문은 현재 영어로 제공됩니다.

automated codingclassifier validationerror propagation
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