Course ID: | FANR 3000. 2 hours. |
Course Title: | Field Orientation, Measurements, and Sampling in Forestry and Natural Resources |
Course Description: | Introduction to equipment used in the field to navigate across
the landscape and to measure a variety of natural resource
attributes. Basic statistical sampling techniques will be
reviewed and applied in the field to obtain information at a
desired level of precision and statistical confidence level.
Concepts will be presented in lecture and apply during field
labs. Field data will be summarized and evaluated to create
reports of field findings. |
Oasis Title: | Field Orientation Measurements |
Duplicate Credit: | Not open to students with credit in FORS 4050, FORS 6050 |
Prerequisite: | Enrollment in Professional Program of Warnell |
Corequisite: | FANR 3000L |
Semester Course Offered: | Offered fall and spring semester every year. |
Grading System: | A-F (Traditional) |
|
Course Objectives: | By the end of the semester, students will have the following
skills.
A. Identify and use appropriate techniques for collecting,
analyzing, testing, and interpreting natural resource data.
1. Understand appropriate methods for sampling terrestrial and
aquatic habitats.
a. Be aware of potential sources of measurement error and bias
and know proper measurement techniques to minimize error.
b. Understand the proper methods for summarizing field data from
these measurement techniques, expanding estimates to a per-acre
or per-hectare basis, and reporting it appropriately to users.
c. Be able to design a simple multi-resource inventory for a
forested property for a target level of estimation for a given
stand measure.
2. Be able to analyze natural resource data and apply
appropriate statistical techniques. [Faculty from all majors
are expected to provide examples.]
a. Sampling of populations (nesting, stratification,
randomization).
b. Development of descriptive statistics (mean, sdev, cv,
stderror, bounds, etc.).
c. Estimation of population parameters and error bounds.
d. Hypothesis testing -- testing for differences and change.
e. Understanding variability, reliability – confidence in the
numbers, confidence limits, measurement error, sample size
requirements.
f. Using simple linear regression to fit a line to paired
observations. |
Topical Outline: | Statistical Concepts [illustrated with examples from across the
disciplines in the WSFR.]
Populations, samples, inference, sample units, sampling frame.
Qualitative and quantitative data summarization / analysis.
Types of data and their descriptions.
Point estimators and inference.
Measures of relative standing, shape, variation, and dispersion
of data.
Interval estimators and inference.
Simple random sampling and Systematic sampling.
Sample size requirements.
Expansion of estimates.
Estimation of population proportions.
Linear regression.
Tests of significance - differences among means, regression
parameters. |