Instructor........Mike
Benedetti
Office...............220 DeLoach Hall
Phone...............910-962-7650
Email................benedettim@uncw.edu
Office Hours....MW 1:00-3:00, or by appointment.
Catalogue Description. GGY
222. Quantitative Methods in Earth Sciences (3) Use and
interpretation of statistical techniques in geographic and geologic
research.
The course emphasizes problem identification, data collection and
interpretation through assignments covering specific kinds of
statistical
methods.
Lecture. MWF
11:00-11:50, DeLoach Hall 114. This course includes lectures,
PowerPoint
demonstrations, and example problems. We will move as quickly as
possible
through the course topics, adjusting the pace as necessary. Therefore,
your
attendance is essential to keep track of assignments, to be informed
about
schedule changes, and to identify problem areas before the exams.
Students are responsible for keeping current with course topics and due
dates
as announced in class and updated to the course web site. If you
miss a
class, please arrange to get the notes from a fellow student.
Prerequisites and Purpose.
This course is intended as an introduction to statistical methods
for
geographers and others in the earth and environmental sciences.
No prior
course work in statistics is necessary. A basic understanding of
algebra
is assumed. This course meets the quantitative skills requirement
in Geography
and Environmental Studies.
Textbook and Course Web Site.
J.C. McGrew and C.B. Monroe, 2009. An Introduction to
Statistical
Problem Solving in Geography (2nd ed.), Waveland Press, Long Grove,
IL.
The textbook includes explanations of course topics, practical
examples
to follow, and statistical tables and formulas.
Problem sets, lecture notes, and helpful tables will be posted
regularly
to the course web site.
Exams.
Each exam will involve definitions, short answers, and problem
solving.
The necessary statistical equations and tables will be provided, and
students
should bring a calculator to the exams. The 2nd exam is not cumulative
- it
will only cover material presented since the 1st exam.
Problem
Sets. Roughly 6-8 homework assignments will be given
during the
semester. The problem sets will give students a chance to
practice the
statistical methods discussed in class, to develop some basic
statistical
computing skills, and to interpret the results of statistical
analysis.
Students are encouraged to work in groups, but each student must hand
in
his/her own finished assignment. The assignments will be graded
on
correct answers and methods, so hand in all your work with each
assignment,
including your calculations and explanations of your reasoning.
Data
Projects. Two
extended problem sets will be given
asking students to collect and analyze their own data sets. The midterm data project deals with spatial
statistics and nearest neighbor analysis, while the final data project
will
cover sampling, estimation, and hypothesis testing.
These are essentially take-home exams that
give students a chance to practice hands-on sampling, analysis, and
interpretation. Data for these projects
may be derived from
coursework or textbooks in your classes, atlases and other reference
books, or
web sites and online databases.
Grading. Your
course grade will be based on 2 exams and between 6-8 problem sets.
50 % Homework Problem Sets (plus one extra
credit problem set)
30% Exams
(midterm in late September, final in early November)
20
% Data Projects (midterm due in
early
October, final due during final week)
Calculators
and Computers. Students should purchase a calculator with
statistical functions for use on problem sets and during exams.
Look for
a statistical calculator with keys such as Σ, μ, σ, n, or STAT. A
good,
cheap model is the TI-36 from Texas Instruments, available in stores
for about
$25. We will discuss the use of statistical calculators in class, but
students
are ultimately responsible for learning to use their own
calculator. We
will also use Microsoft Excel to perform statistical analysis for
several
problem sets during the semester.
Course
Topics:
Topics
to be covered on the first mid-term exam:
Ch. 1-2: Introduction (basic vocabulary, notation, measurement levels,
graphical methods)
Ch. 3: Descriptive Statistics (measures of centrality, spread, and
shape)
Ch. 4: Descriptive Spatial Statistics (measures of location, distance,
and
dispersion)
Topics
to be covered on the second mid-term exam:
Ch. 5: Probability (postulates and theorems, random variables,
probability
distributions)
Ch. 6: Sampling (random samples, sampling distributions, spatial
sampling)
Ch. 7: Estimation (confidence intervals for estimates of population
mean or proportion)
Topics
to be covered on problem sets after the second mid-term:
Ch. 8: Basic Hypothesis Testing (one-sample tests for difference of
means or
proportions)
Ch. 9-10: Multiple-Sample Hypothesis Testing (2-sample tests, ANOVA
methods)
Ch. 13: Correlation (covariance, measures of correlation, spatial
correlation)