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About This Course



Geological Data Analysis has been taught at the University of Houston for more than 25 years. The course has evolved from a main frame-based course to one in which all of the work is done on desk top computers. The latest stage in the evolution of this course is a change in design so that formal class meetings are reduced and Internet-based resources provide much of the background necessary to introduce a number of statistical models used in exploring geological data. The models used are essentially those discussed on 25 years ago whereas the way in which the models are presented to the class has changed dramatically.

Although not necessary, the instructor prefers to create an environment in which class members are new employees of Geological Analytical Services - GAS. Our moto is:

Got a problem?
Don't let it pass
Give us a call ....
Get relief from GAS

The course will meet a number of times during the semester; dates for formal meetings are given in bold on the reading list. Although the instructor will be available in person or via telephone, the intent is to use e-mail for discussions and submission of reports.

The course consists of the following components:

  1. Assigned Readings -- Related readings are drawn from various courses which have Internet-based resources. This tends to make the readings somewhat disjointed but the material is quite good. These readings along with the text should provide the background needed to complete the exercises. Some of the readings contain exercises. Although I will not require you to hand in answers, you can learn a lot by trying them. The last half of the readings focus on ways to portray data. This will be a key component of the short project that you will do at the end of the course.

    I will distribute copies of an out-of-print text on the first day of class. It is up to you to read the appropriate material.

  2. All of the software needed is installed in the Geosciences Computer Cluster in the SR Building. This year we will use Data Desk for which I have purchased five site licenses. Four of the macs in our cluster will have the applications. You may find it to your advantage to purchase your own copy of the application. You may buy a single, non transferrable Professional Version for about $100. If you have a computer where you live and would prefer to do all of your work there, recall that there is no textbook to purchase.....use those funds to buy the application. By the way, I get no cut of your purchase!

  3. Exercises -- There are a number of exercises to be completed. Some are standalone whereas others are related. The last exercise (given out in early December) will constitute the final examination. Exercises will count for 60% of the final grade. Each exercise is accompanied by one or more readings chosen to give you some additional background or to point out some facet of the analytical technique.

  4. Demonstrations -- The Internet-based materials are rich in interactive exercises. This can be an effective way to learn. Spend as much time as you need to "get the point".

  5. E-mail Quizes -- Several times during the semester a problem set will be distributed to the class via e-mail. A due date will be given at the time of assignment. Quizes will count for 20% of the final grade.

  6. Short Project -- By October 15 each employee will identify a data set which will serve as the basis of a short project. The data set must be described and problems identified. Emphasis should be on ways to portray the data and results of analyses undertaken to better understand the data. I will evaluate the project and give approval or suggest modifications. Employees should select data which is of personal interest. These can be data gathered by the employees or drawn from the literature. Projects will count for 20% of the final grade and will be due on on the date on which the final examination is scheduled.

In general, the class will be encouraged to work together but each one should prepare his/her own report. Projects which are to be completed individually will be identified.

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