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i# project-iota STAT 159/259: Reproducible and Collaborative Statistical Data Science

Fall 2015 UC Berkeley

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This repository contains reproducible analysis based on dataset used in [Working Memory in Healthy and Schizophrenic Individuals] (https://openfmri.org/dataset/ds000115).

Installation

  1. Clone our project repository: https://github.com/berkeley-stat159/project-iota
  2. Install python modules with pip: pip install -r requirements.txt

General steps:

Download Dataset

  • make dataset: Download the 4.2GB ds115_sub001-005.tgz and nipy.bic.berkeley.edu, then automatically unzip sub001, the only subject data that we worked with.

Generate Convolution

  • make convo: Convolve study conditions with hemodynamic function(HDF). Included are the regular block design convolutions as well as a higher resolution convolutions for event-related convolutions.

Modeling & Analysis

  • make modeling: Run all the regressions and related plots mentioned in our report.

Hypothesis Testing

  • make testing: Run all the hypothesis tests and validations of our mode.

Report

  • make report: Compile our final report with analysis results.

Thanks to Jarrod Millman, Matthew Brett, [Ross Barnowski] (https://github.com/rossbar) and [J-B Poline] (https://github.com/jbpoline) for their instructions throughout the semester.

Contributors