Editing Statistics and Statistical Programming (Fall 2020) (section)

==== Overview ====
As a demonstration of your learning in this course, you will design and carry out a quantitative research project, start to finish. This means you will all:

* '''Design and describe a plan for a study''' — The study you design should involve quantitative analysis and should be something you can complete at least a first pass on during this quarter.
* '''Find a dataset''' — Very quickly, you should identify a dataset you will use to complete this project. For most of you, I suspect you will be engaging in secondary data analysis or a analysis of a previously collected dataset.
* '''Engage in descriptive data analysis''' — Use R to calculate descriptive statistics and visualizations to describe your data.
* '''Motivate and test at least one hypothesis about relationships between two or more variables''' — I'm happy to discuss alternatives to formal hypothesis testing procedures (even if some of them are beyond the scope of this course). 
* '''Report and interpret your findings''' — You will do this in both a short paper and a short (recorded) presentation.
* '''Ensure that your work is replicable''' — You will need to provide code and data for your analysis in a way that makes your work replicable by other researchers.

''I strongly urge you'' to produce a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, use as pilot analysis that you can report in a grant or thesis proposal, and/or use to fulfill a degree requirement.

There are several intermediate milestones, deliverables, and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Canvas by 5pm CT on the day they are due.