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  • DDH
  • General
  • Module A (0/4) - intro to biomedical informatics and health information systems
  • Module A (1/4) - Relational databases
  • Module A (2/4) - Biomedical ontologies and terminologies
  • Module A (3/4) - Electronic health data capture
  • Module A (4/4) - Data models, standards and interoperability
  • Module A (Final live) - merge it all together and wrap-up of Module A
  • Statistics Textbook
  • Module B (1/6) - Lect 1 Descriptive Graphical Analysis
  • Module B (2/6) - Lect 2 Describing Numerical Data
  • Exercise Excel on descriptive statistics #1-Due by 6th of May
  • Exercise Excel on descriptive statistics #2-Due by 6th of May
  • Module B (3/6) - Lect 3 Inferential Theory
  • Exercise Excel on inferential statistics #3-Due by 6th of May
  • LIve lecture 1 - Mod B
  • Rules for the final exam
  • Module B (4/6) - Lect 4 Hypothesis Test_I
  • Module B (5/6) - Lect 4 Hypothesis Test_II
  • Module B (6/6) - Lect 4 Contingency Tables Analysis
  • Live Lecture 2 - Mod B
  • Final exam Dataset
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Data Driven Healthcare

  1. Home
  2. Courses
  3. AI
  4. DDH
  5. Live Lecture 2 - Mod B
  6. Python script

Python script

    • datasetdataset
      • 500_Person_Gender_Height_Weight_Index.csv500_Person_Gender_Height_Weight_Index.csv
      • height_anova2.xlsxheight_anova2.xlsx
    • DatasetsDatasets
      • data_description.txtdata_description.txt
      • datasets.mddatasets.md
      • test.csvtest.csv
      • train.csvtrain.csv
    • Analysis of Variance and Chi-Squared Test.ipynbAnalysis of Variance and Chi-Squared Test.ipynb
    • Anova_extra_example.ipynbAnova_extra_example.ipynb
    • Descriptive Statistics_final.ipynbDescriptive Statistics_final.ipynb
    • Hypothesis Testing.ipynbHypothesis Testing.ipynb
    • Inferential Statistics_modified.ipynbInferential Statistics_modified.ipynb
◄ Anova Analysis
Live Lecture 2 ►
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DDH
Data retention summary