Data analysis and Geostatistics

2022

 
 

Statistical techniques provide powerful tools for analyzing and interpreting data, and in this course you will become familiar with the most commonly used techniques to analyze data in the Earth Sciences. Starting with the most basic statistical parameters we will gradually move to more complicated multivariate techniques, including cluster analysis, factor analysis and (multiple) regression.


The course consists of a set of lectures and practical sessions where the tools introduced in the lectures will be applied to a geological data set. Many statistical parameters and plots can be prepared using a spreadsheet program, but for more advanced statistical analyses we will use the PAST statistics package. It is assumed that you are intimately familiar with analyzing data in spreadsheet programs such as Excel, Calc or QuattroPro, and setting up formulae and functions in these programs. If you need to refresh this, most spreadsheet programs offer help files, both offline and online (for example: Excel and Calc). Details of the lab can be found here, and lectures will be posted here after each session.


The course will mainly focus on the fields of data analysis and statistical testing and modeling. Some aspects of probability analysis will be addressed as well, mainly in relation to confidence intervals and the concept of “statistical proof”. Of further interest is the issue of impartiality of the observer in geological studies as exemplified in the 3-door problem.


A full overview of the course can be found here.


The book that we will use for the course is “An introduction to geological data analysis” by Swan and Sandilands (Blackwell publishing, ISBN 0632032243). The main advantage of this book over standard statistics textbooks is that it is tuned specifically to statistical techniques relevant to the Earth Sciences. Unfortunately, the book is no longer in print, but second-hand copies are readily available online. The following chapters should be studied;


    chapter 1:    completely

    chapter 2:    2.1, 2.2, 2.4 (except 2.4.5.3/4), 2.5, 2.6 up to 2.6.2.3

    chapter 3:    up to 3.3.2

    chapter 4:    completely

    chapter 7:    7.1 & 7.2 (general concepts only), 7.3, 7.4.3

    chapter 8;    8.1.1, 8.1.2, 8.3, 8.4, 8.5, 8.6 (general concepts only)


There are also many excellent online resources on statistics and data analysis, including a full textbook by the creators of the Statistica software.

Data analysis and Geostatistics

on the use of statistical techniques in the Earth Sciences

Course schedule

- lectures:

  Thu 10:00 - 12:00 in 315

- labs:   

   Tue 9:30 - 12:30 in 315

Clockwise from top; the Kawah Ijen cra-ter lake in Java, Indonesia; geological map of the Desges valley, French Massif Central; tourmaline-biotite thermometer with uncertainty in formulation and data.


Copyright:     Vincent van Hinsberg & Simon Vriend


Last updated:     March 2022

Examination

- written midterm:

  20% of mark

- formal written exam:

  40% of mark

- data analysis project:   

   40% of mark, groups of 3

    consists of analyzing a large       

    geological data set using a

    variety of statistical methods

Course prerequisites

There are no formal prerequisites for this course, but a thorough knowled-ge of spreadsheet programs and their (statistical) functions is assumed

Final exam

April 13, 9:00 - 12:00 in FDA 315