# Applications and Broader Impact: Sampling and Monte Carlo

:::{admonition} Draft chapter
:class: warning
This chapter collects the broader-impact discussion and readings that accompanied Part II in AM207 (Harvard, Fall 2021). It will be expanded into a full chapter.
:::

## Readings

**Applications and Broader Impact**

- [Small Data Can Play a Big Role in AI](https://hbr.org/2020/02/small-data-can-play-a-big-role-in-ai)
- [Incorporating Bayesian Ideas into Health-Care Evaluation](https://webuser.bus.umich.edu/feinf/Bayes/Spiegelhalter_-_Incorporating_Bayesian_Ideas_Into_Health-Care_Evaluation.pdf)
- [A Bayesian Modelling Approach with Balancing Informative Prior for Analysing Imbalanced Data](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152700)
- [On Using Bayesian Methods to Address Small Sample Problems](https://www.tandfonline.com/doi/abs/10.1080/10705511.2016.1186549?journalCode=hsem20)
- [Item Response Theory for assessing students and questions (pt. 1)](https://medium.com/@lucabenedetto/advantages-in-using-item-response-theory-for-assessing-students-and-more-4a9665258863)
- [Simultaneous Discovery, Estimation and Prediction Analysis of Complex Traits Using a Bayesian Mixture Model](https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004969)
- [Parkinson’s Disease Subtypes in the Oxford Parkinson Disease Centre (OPDC) Discovery Cohort](https://content.iospress.com/articles/journal-of-parkinsons-disease/jpd140523)
- [One Size Doesn’t Fit All: Using Factor Analysis to Gather Validity Evidence When Using Surveys in Your Research](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6757227/)