Project Peer Review

due Tues, Nov 23 at 11:59pm

Critically reviewing others’ work is a crucial part of the scientific process, and STA 199 is no exception. Each group has been given read access to another group’s repo to review and provide feedback on their project draft. This review is intended to help you create a high quality final project, as well as give you experience reading and constructively critiquing the work of others.

To ensure the group has enough time to start incorporating feedback ,you should work on the peer review during lab and submit comments by Tuesday, November 23 at 11:59pm.

Getting started

In GitHub, search the repositories for project, and you should see the repo for the project you’re reviewing. You will be able to read the files in the repo and post issues, but you cannot push changes to the repo. You will have access to the repo until the deadline for the peer review.

Reviewing the draft

Carefully read the project draft, and consider the questions below as you read it.

Once you’ve read the draft, you will submit the review for each part by opening new Issues in the team’s repo. To open and submit an issue: - Go to the team’s repo and click Issues.

Peer review questions

Your response to each question in the peer review has two parts:

1️⃣ Selection of one of the following:

2️⃣ Brief comment about your selection.

Issue 1: Introduction + Data

Issue 2: Exploratory data analysis

Issue 3: Methodology + Results

Issue 4: Writing + Reproducibility

Applying what you’ve learned to your project

Discuss the following as a group. You do not need to submit a response to this question.

After giving feedback to this group, what is one thing you want to change or continue working on for your report?

Submission

The peer review will be graded on the extent to which it comprehensively and constructively addresses the components of the partner team’s report: the research context and motivation, exploratory data analysis, reproducibility, and any inference, modeling, or conclusions.

You will be graded based on the feedback in the issues submitted on GitHub.