**Course intent**:
The objective of this course is to provide students with basic
data analysis, quantitative and computer skills increasingly necessary
to succeed in geoscience careers, and in many other career paths.
Similar courses at other institutes are commonly
taught as an upper division course, but it also makes sense to
acquire these skills early and build on them in subsequent geology
courses, which is the approach taken here. Some of the software
you will be introduced to includes Adobe Illustrator and Photoshop,
ArcGIS, Excel, Surfer, and Visual Basic for Applications. In addition,
the course should familiarize the student with department and
university analytic resources, and with a variety data sources available on the web. As an important byproduct students will also learn a fair bit
of geoscience, as the focus is on working on geoscience problems.

Specific topics covered include: describing and comparing sample populations, simple data manipulations, data visualization, creating and working with databases, surface contouring and modeling, fractal geometries and distributions, exponential behavior, basic GIS principles, analysis of remotely sensed data, graphic data representation, and simple computer modeling of geologic processes. If these topics are unfamiliar to you, that is to be expected. In all cases examples and exercises will involve geoscience data, but geoscience provides a large umbrella. For many exercises you can chose to work with data that matches your more specific interests.

Science has changed immensely in the last two decades. Before data and information was primarily in hard copy, assembling it took significant effort, and it was helpful to have as much in your head as possible. Now, so much is easily found and available with the web and the great variety of search engines and large public data bases that the focus has shifted to the sifting through and analysis of all that information; in other words the challenge is often in how to create knowledge out of all that data. It is developing these analytic skills that this course focuses on.

**Student audience**:
The intended student audience consists of geology, geography and
environmental science majors who are in the first or second year
of their program. They should have successfully completed at least one introductory course in geoscience. Students minoring in these areas may also want
to take this course, as may education majors obtaining endorsements
in earth or natural science.

**Prerequisite:** The prerequisite is one course in earth science of some sort. This could be one of the following: GEOL1010, GEOL 1100,
GEOL1170, GEOG1030, GEOG1060, or GEOG1070. Other courses that
give the student a background in physical earth science would
be acceptable on a case by case basis. Please do not hesitate
to talk to the instructor if you have a question in this regard.

**Texts**: There
is not an appropriate text to assign for this course, and instead the material available at this website will be your text. Readings
from a variety of sources will also be assigned. Two good reference books that are
suggested for the course and for future geoscience work are:

- McKillup, S. & Dyar, M. D., 2010, Geostatistics Explained - An Introductory Guide for Earth Scientists; Cambridge Press, 396 p.
- Swan, A. R. H. & Sandilands, M., 1995, Introduction to geological data analysis; Blackwell Science, 446 p..
- other useful references.

**Grading**:
There will be a total of 150 points possible, 10 for each of the
14 weeks of exercise, and 10 points for the final (which will be a multiple
choice exam). The grade bins are as follows:

- 150 -142 = A+
- 142 -134 = A
- 134 -126 = A-
- 126 -118 = B+
- 118 -110 = B
- 110 - 102 = B-
- 102 - 94 = C+
- 94 - 86 = C
- 86 -78 = C-
- < 78 -you don't want to be there!

**Late assignments** will be taken, but with a
1 point penalty if less than a week late and a 2 point penalty
if more. All late assignments need to be in by Friday, noon, of deadweek (the week before finals).

**While you are encouraged to help each other,
the final product must clearly reflect your own work and understanding**.
The penalty for cheating will be failure for the course, and the
stigma associated with cheating. It just isn't worth it, and it
isn't necessary, especially in this course. If you have a question about what might constitute cheating please ask me.

Clearly the majority of your effort should go into the weekly assignments. When group work is involved, based on peer evaluation, and with instructor input, students will be awarded points for the degree they constructively contributed to the group's effort.

The course content at this website will be continually updated throughout the semester as part of a continuous improvement process.

**Back your work up on a regular basis, and keep copies of all your work!** The computer lab may be reimaged at any time, and anything saved on these machines will be lost.

**Week 1: ****Introduction to course:**

- introduction to course content and objectives, and computer lab facilities and policies.
- course text books, other references and information.
- review of topics covered in the course and relevance to the discipline
- types of data, and data and software sources.
- professional behavior.
- Exercise 1.

**Week 2****: Identifying , describing and comparing populations:**

- description of histograms, rose and other frequency diagrams.
- summary statistics..
- comparative tests (e.g Chi Square).
- example of an analysis of a data set in Excel.
- Exercise 2.

**Week 3****: Classical linear and curvilinear regression**:

- simple linear regression.
- significance of R-squared.
- simple transformations (e.g. log), and normalization.
- example of an analysis of flood recurrence interval vs. discharge.
- cautions on extrapolations.
- Exercise 3.

**Week 4****: Analysis of fractal geometries in the geosciences:**

- definition of fractal geometry.
- log-log size vs. frequency plots and the fractal dimension.
- examples of fractal geometries in earth science (Turcotte, 1992).
- use of fractal relationships in filling in information or resolution gaps, in risk assessment, and in modeling.
- Exercise 4.

**Week 5****: Surface analysis and modeling**:

- types of and use of 'surface' diagrams in earth science.
- gridding and interpolation procedures.
- introduction to contouring software packages (e.g. Surface3).
- 3-d transect diagrams and visualization elements.
- derivative surfaces.
- example from data to contour and transect diagrams of groundwater tables and of associated flow nets.
- Exercise 5.

**Week 6****: Computer aided map construction:**

- imp. of maps and cross sections as data models.
- basic components and principles of map construction.
- sources of base maps, including the web.
- computer maps and linked databases (this way to GIS).
- common software packages used to compile maps (will focus on Adobe Illustrator).
- examples of different types of maps.
- Exercise 6.

**Week
7****: Analysis of imagery:**

- scales of application: can be applied to satellite or thin section imagery.
- sources of imagery.
- image distortion and rectification.
- spectral analysis, and classification.
- variety of related software will be introduced.
- examples of use of imagery in resource exploration and management.
- Exercise 7.

**Week 8****: Geoscience databases:**

- basics of database structure.
- querying and manipulating databases.
- relevant software.
- metadata.
- Exercise 8.

**Week 9****: Complex systems, multiple data sets and Geographic
Information Science**:

- introduction to Stella software for modeling complex systems.
- examples of problems requiring management of multiple data sets explored (e.g. land fill siting, groundwater flow modeling, mineral exploration).
- basic approach of Geographic Information Science described.
- DEMs
- common software packages described.
- vector vs. rastor based representation will be explored.
- tour of departments GIS facilities.
- examples of GIS products explored.
- Exercise 9.

**Week 10****: Modeling with exponential and power law functions
(see Vacher 2000):**

- basics of equations and equation manipulations.
- examples of geologic phenomena that display this non-linear behavior.
- Exercise 10.

**Week 11 &
12**** : Computer modeling of earth
processes - Visual Basic for Applications in Excel, and Stella.**

- uses of computer modeling in geosciences.
- intro to programming languages typically used in geoscience modeling (Visual Basic, C++).
- Students will be introduced to the basic design and approach behind VBA, and Visual Basic.
- Introduction to Stella.
- Exercise 11.

**Week 13****: Temporal spectral analysis:**

- examples of temporal earth science data: e.g. tree ring thicknesses, facies changes in a stratigraphic column, growth structures in fossils.
- explanations for cyclicity (e.g. Milankovich cycles).
- Markov Chain analysis.
- tests for cyclicity vs. randomness.
- examples from the literature (Swan and Sandilands, 1995).
- Exercise 13.

**Week 14****: Classification of data using fuzzy logic**:

- concepts of fuzzy sets, expert rules and fuzzy measures will be introduced.
- examples will be given of fuzzy sets, and expert rules (e.g. in sedimentary facies classification, in hand specimen mineral identification).
- Exercise 14.

**Week 15**: **Wrap up.**

- importance of knowing about garbage in - garbage out.
- context of skills in geoscience.
- class evaluations.

We are very fortunate to have a relatively newly outfitted computer lab in (DSC room 290), which is where we will spend much of our time. However, it is beneficial to learn to use and migrate between different platforms, different operating systems, and different software versions, which is more and more the practice in the real world. One frustration in courses like this is when the computer or program doesn't work right or just as expected, or you have hit a roadblock. The key is to get help!

Remember to log out when you are finished. Use the machines in DSC 290 only for course work. Do not have drinks or food within spill reach of the computers.

Also, I am always interested in feedback on the course. Please let me know whatever is unclear to you (i.e. you are highly encouraged to ask questions). Thank you.

Survey of student backgrounds.

Last updated 8/17/2010. Copyright by Harmon D. Maher Jr.. This material may be used for non-profit educational purposes if proper attribution is given. Otherwise please contact Harmon D. Maher Jr.