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.
Lecture. MWF
11:00-11:50, 101 DeLoach Hall. Attendance is expected. If
you are
going to miss a class, please arrange to get the notes from a fellow
student. We will move as quickly as possible through the course
topics,
adjusting the pace when 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.
Prerequisites and Purpose.
This course is intended as an introduction to statistical methods
for
geographers and others in the earth and environmental sciences.
There is
no prerequisite, and no prior course work in statistics is
necessary. A
basic understanding of algebra is assumed. This course meets the
quantitative skills requirement for Geography and Environmental Studies
majors
(equivalent to STT 215).
Textbook. J.C.
McGrew and C.B. Monroe, 2009. An Introduction to Statistical
Problem
Solving in Geography (2nd ed.), Waveland Press, Long Grove, IL.
Includes
explanations of course topics, practical examples to follow, and
statistical
tables and formulas.
Grading. Your
course grade will be based on 2 exams and 6-8 problem sets.
15 % Exam 1
15 % Exam 2
45 % Homework Problem Sets
10
% Midterm Data Project
10 % Final Data Project
5
% Instructor's Discretion (attendance, participation, effort)
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 the final data project will cover hypothesis testing. These are essentially take-home exams that
give students a chance to practice hands-on sampling, data analysis,
and
interpretation of results.
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. I
suggest
the TI-36 calculator from Texas Instruments - you shouldn’t have to pay
more
than about $30. (NOTE: You do not need a programmable
financial
calculator for this class.) 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. 9-11: Multiple-Sample Hypothesis Testing (2-sample tests, ANOVA
methods)
Ch. 13: Correlation (covariance, measures of correlation, spatial
correlation)