透過分析決策學習 ENA。

重設

33 節課

頁 4 / 6

詮釋中階35 分鐘2026年8月5日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

effect sizeconfidence intervalcoordinate comparison
開啟教程
研究設計中階35 分鐘2026年8月6日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

multiple groupsplanned contrastsmultiplicity
開啟教程
建模中階35 分鐘2026年8月7日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

longitudinal trajectoryshared spacetime ordering
開啟教程
建模中階35 分鐘2026年8月8日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

ordered network analysisdirected edgessequence
開啟教程
資料準備中階35 分鐘2026年8月10日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

multimodal dataevent alignmentsensor traces
開啟教程
資料準備中階35 分鐘2026年8月11日
ENA 學院課程 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.

經審核的教程正文目前以英文提供。

automated codingclassifier validationerror propagation
開啟教程