Advanced Data Analysis Workshop
last updated November 22, 2013
This workshop course is custom designed around your statistical
analysis goals. We will begin with short descriptive
presentations by course participants which identify a scientific
working hypothesis, statistical null hypothesis and analysis goal
for the semester. Based on these presentations, I will work
individually with each participant to design and implement a
semester-long statistical analysis project. Ideally
this work will contribute directly to your thesis or dissertation
work. We will meet weekly and individually to discuss
progress and plan next steps. At the end of the semester,
students will present and defend their results and interpretation
in class. Because of the nature of the course, participation
is limited to a maximum of 10 students.
the conclusion of the semester, students should be able to:
- Develop code, evaluate and interpret statistical analyses
specific to their thesis/dissertation research, given
- Present and defend their results and interpretations for a
general geosciences audience.
Location and Time: BPS
1228, Tu 2:00-4:45p.
Instructor: Michael Evans , Department of Geology and ESSIC , Chemistry
Bldg, Rm 1212B. ph 301-405-8763; email: email@example.com.
Office hours: TBD and by email. Class sessions will
effectively be like office hours. I will try to answer emails
between class sessions within 24 hours, and reserve the right to
copy the class on replies of interest/benefit to all.
Prerequisites: A research dataset (observations or
simulations) to be studied over the course of the semester, and
permission of the instructor.
Reading and course materials: There is no textbook
required for this course. Per copyright fair use guidelines,
we will identify and share readings electronically as password
protected PDF files, served from this webpage, as necessary.
Assessment (subject to
- Initial presentation: 20%
- Clear presentation of the research problem via a specific,
testable, predictive scientific working hypothesis and
associated specific, testable, predictive statistical null
- An evaluation rubric is here.
- Weekly progress reports: 50%
- Co-development of statistical analysis and steady
advancement toward the semester analysis goals.
- Final presentation: 30%.
- Recapitulation of scientific working hypothesis and
statistical null hypothesis
- Clearly communicated results, and interpretation, given
- An evaluation rubric is here.
- Final grades as reported to the Registrar via UMEG system will
Statistical background is available from the following excellent
sources, some of which I have available for short-term loan
(links to commercial vendors are convenient descriptors and give
access to tables of contents, but are not intended to be sales
- J.C. Davis, 2002: Statistics
and Data Analysis in Geology (3rd edition).
- D.S. Wilks, 2006: Statistical
Analysis in the Atmospheric Sciences (2nd ed).
- R.R. Sokal and J.F. Rohlf, 1995: Biometry:
The Principles and Practice of Statistics in Biological
Research (3rd ed).
- P. Bevington and D.K. Robinson, 2002: Data
reduction and error analysis for the physical sciences,
- Taylor, 1982: An
introduction to error analysis (1st ed).
- A link to ISI Web of Science (UMD ID required for access) is here.
- You are free to work in whatever computing environment you
like, but know that:
- Matlab will be
available for you to use on Geology Computing Lab computers.
- Octave, an open-source,
freeware Matlab workalike, is downloadable here.
- Academic deadlines (UMD):
- Absences: To make the most of in-class activities and
opportunity for discussion, you are expected to attend class
regularly. Absences from graded assignments will not be
excused except for those causes approved by University
policy. Please make all efforts to let me know of
excused absences well ahead of time; scheduling issues
pertaining to the final absolutely must be resolved in advance.
- Academic Accommodations: If you have a documented
disability, you should contact Disability Support Services
(DSS), 0126 Shoemaker Hall. Each semester students with
documented disabilities should apply to DSS for accommodation
request forms which you can provide to your professors as proof
of your eligibility for accommodations. The rules for
eligibility and the types of accommodations a student may
request can be reviewed on the DSS web site.
- Religious Observances: The University System of
Maryland policy provides that students should not be penalized
because of observances of their religious beliefs; students
shall be given an opportunity, whenever feasible, to make up
within a reasonable time any academic assignment that is missed
due to individual participation in religious observances. It is
the responsibility of the student to inform the instructor of
any intended absences for religious observances in writing
within the first two weeks of the semester.
- Honor Code: The Student Honor Council observes that,
"The University of Maryland, College Park has a nationally
recognized Code of Academic Integrity, administered by the
Student Honor Council. This Code sets standards for academic
integrity at Maryland for all undergraduate and graduate
students. As a student you are responsible for upholding these
standards for this course. It is very important for you to be
aware of the consequences of cheating, fabrication,
facilitation, and plagiarism. For more information on the Code
of Academic Integrity see the website of the Student Honor
Council. Any evidence of dishonesty on any graded
assignment will result in a referral to the Office of Student
- Mid-semester Course
evaluations: Because I like to receive input while it
can still be used to improve the course for you, we may have an
informal, anonymous mid-semester course evaluation following the
midterm exam. I will respond to this evaluation before
beginning of the second half of the semester.
- Results of an informal mid-semester course evaluation will
- Course Evaluations: You will be notified when CourseEvalUM will
be open for course evaluations in the spring (for N>=5
- The expectation is that all students will complete these.
This is YOUR chance to anonymously evaluate this class: please
use this opportunity!
- Students who complete evaluations for all of their courses
in the previous semester (excluding summer), can access the
posted results via Testudo's CourseEvalUM Reporting link for
any course section on campus that has at least a 70% response
rate and more than 4 participants.
- You can find more information, including periodic updates,
at the IRPA
course evaluation website.
Schedule (subject to
revision -- refresh page for latest update)
Scientific working hypothesis, statistical null hypothesis
|Feb 11, 18, 25;
Mar 4, 11, 25;
Apr 2, 9, , 23, 30
|Guided inquiry: individual