Basic aim

A basic aim of the course is for all students to work toward a final paper that is suitable for submission to an applied statistics journal.

“Working toward” a final paper that is suitable for submission to an applied statistics journal means just that: by semester end you, as a student in the class, may not yet have a final draft that could be submitted to a journal, yet the aim is to have made substantial progress in achieving that.

Research process

The research process is inherently flexible and cyclic and generally involves the following broad steps:

• Which question or questions are you investigating (the Research Question(s))
• Why are these questions worth investigating? (the Rationale)
• Who else has done anything relevant? (the Literature Review)
• How will you go about answering the research questions? (the Method)
• What did you find (the Results)
• So what? (Conclusions and Discussion)

Working alone or in a team

Students in the class can choose to work alone or in a team.
Generally, working in a team can be very helpful in that team members working cooperatively can usually generate many more productive re-search questions and ideas that a single person working alone.

However, working alone is perfectly acceptable if that is your choice

Types of applied statistical research

Applied statistical research can involve collecting and analyzing data, developing new techniques for analyzing data, or analyzing publicly available data sets.

Generally, obtaining new data sets through an appropriate experimental design is a lengthy and somewhat complicated process. Once the data is collected – a valuable and reportable and useful addition to the applied statistical literature in itself – there is then the issue of analyzing the data.

Much more straightforward is to use a publicly available data set and generate productive research questions about that data set.

Another productive avenue of research is to review the applied statistical research literature on a topic of interest.

Alternatively, you may want to focus on developing new, or modified, techniques for analyzing data in a certain way. Much literature in applied statistics is devoted to just this process.