AMS 575, Internship in statistical Consulting
Directed quantitative research problem in conjunction with currently existing research programs outside the department. Students specializing in a particular area work on a problem from that area; others work on problems related to their interests, if possible. Efficient and effective use of computers. Each student gives at least one informal lecture to his or her colleagues on a research problem and its statistical aspects. 
Prerequisite: Permission of instructor
1-9 credits, ABCF grading 

Text: No text

Fall and Spring Semesters

Learning Outcomes:

1) Demonstrate skills applying knowledge learned from the following classes to real or realistic data analysis projects (*the students are recommended to take AMS 575 after completing at least 3 of the following courses):
     AMS 572, Data Analysis I;
     AMS 573 Categorical Data Analysis;
     AMS 577 Multivariate Analysis;
     AMS 578 Regression Analysis;
     AMS 582 Experimental Design;
     AMS 586 Time Series Analysis;
     AMS 588 Biostatistics (covering Survival Analysis, and Clinical Trials);
    AMS 597 Statistical Computing.

2) Learn how to join a research project:
      * Become engaged with other members of the project;
      * Learn general background information about project;
       *Communicate with experts who are non-statisticians.

3) Demonstrate the ability to:
      * Initiate statistical consulting assignment(s);
      * Help project leaders develop the statistical design of the  collection of data;
      *Participate in the collection of data, entry, and clean of the data, as appropriate.

4) Demonstrate the skills needed to:
      * Analyze the data;
      * With guidance from project leaders and statistics faculty, choose exploratory and inferential statistical tools to analyze data and test hypotheses;
      * Apply suitable statistical programs/software for data analysis and report writing purposes.

5) Demonstrate the skills needed to communicate statistical findings:
      * Orally to members of research team and to other scientists;
      * In a well written scientific paper.