Module 1 - Lesson 10: Publishing and evaluating studies based on cohort data and analysis of variance

[turukawa]

ETHICS

Appraise the challenges inherent in evaluating and communicating analysis and results.

Analytical models are based on complex data. If any of these are opaque or inaccessible, then the clarity of the outcome is uncertain (or disputed).
Example: Google Flu Trends

CURATION

Discover data for reuse and appreciate the value of data retention beyond the scope for which it was collected or sampled.

Cohort data and open repositories … leading towards the project for this module.
E.g. the various cohort studies (INDEPTH, etc.)

ANALYSIS

Determine appropriate sample sizes and analysis of variance (ANOVA) methods.

Sample sizes, ANOVA, testing means across many groups.

PRESENTATION

Synthesize all you have learned to present new insight from old data.

Prepare students for the project.

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CASE STUDY

Example of coffee and depression (could reverse data to demonstrate what the sample may have looked like, and how it could be spurious).

Student project will be to identify a cohort dataset online, and then study that data to produce a short statistical study. They need to take into account all that they have learned.