**Course Syllabus**** for**

**PlSc 724 - FIELD DESIGN I**

** INSTRUCTOR**: Rich Horsley

*Office *370H Loftsgard Hall or 109 Waldron Hall

*Phone *237-8142

*e-mail*horsley@badlands.nodak.edu

* Course Description*: PlSc 724 is a lecture course that discusses different statistical techniques for the analysis and
interpretation of biological problems. Statistical techniques to be used include analysis of variance, simple linear regression,
and simple correlation. Topics related to the planning of experiment to test hypotheses related to biological problems also are
discussed.

* Prerequisite*: An introductory course in statistics

** Required Text**: Principals and Procedures of Statistics - A Biometrical Approach: 3

* Goals of PlSc 724*: The broad goal for this course is to instruct students how to properly plan experiments, analyze data, and
interpret results associated with testing hypotheses related to biological problems.

**Outcome*** 1* Students will be able to comprehend concepts needed to plan experiments to test hypotheses. These concepts
include experimental error, replication and its function, relative precision, error control, and randomization.

** Outcome 2** Students will comprehend three experimental designs: completely random design, randomized complete block
design, and latin square design. For each design, students will know: the proper randomization procedure, how to describe the
design, advantages and disadvantages, how to partition total degrees of freedom and sources of variation, the linear additive
model, how to write expected mean squares, how to calculate estimates for missing data, how to do the analysis of variance,
how to make tests of significance, and how to interpret results of significance.

* Outcome 3 *Students will be able to choose the correct experimental design to test hypotheses related to biological problems.

** Outcome 4** Students will comprehend the use of simple linear regression to analyze and interpret results from experiments
related to biological problems.

** Outcome 5 **Students will comprehend the use of simple correlation to analyze and interpret results from experiments related to
biological problems.

* Grading*: Homework - ten homework assignments (10%)

Two lecture examinations (25% each)

Final exam - Comprehensive (40%)

This course is graded on a curve. The gradelines for the curve are determined by the level of difficulty of the examinations and homework. Yet, all scores of 90% or above are guaranteed an A, and scores of 80 to 89.9% are guaranteed a B.

__STUDENTS WITH DISABILITIES__

__STATISTICAL REVIEW__

Types of variables

Populations vs. Samples

Three measures of central tendency

Three measures of dispersion

Variance of the mean and standard error

Coefficient of variation

Linear additive model

__PLANNING EXPERIMENTS__

Types of experiments

Items to consider in planning experiments

Experimental units

Replication

Choice of design

Randomization

__HYPOTHESIS TESTING__

Type I error

Type II error

Power of the test

Steps in testing hypotheses

Testing the hypothesis that µ is a specified value (t-test and confidence interval)

__COMPARISONS INVOLVING TWO SAMPLE MEANS__

Two sample means with equal variance (t-test, confidence interval, and F-test)

Two sample means with unequal variance (t-test)

__COMPLETELY RANDOM DESIGN__

ANOVA for any number of groups with equal replication

ANOVA for any number of groups with unequal replication

ANOVA with sampling

Linear models for CRD experiments

Assumptions underlying ANOVA

__MEAN COMPARISON TESTS__

Least Significant difference (lsd)

Duncan's new multiple range test (DMRT)

Testing effects suggested by the data

Orthogonal contrasts

__RANDOMIZED COMPLETE BLOCK DESIGN__

ANOVA for any number of treatments

ANOVA with sampling

Linear models for RCBD experiments

Experimental error in RCBD experiments

__LATIN SQUARE DESIGN__

ANOVA for single square

ANOVA for repeated squares

__REGRESSION AND CORRELATION__

Simple linear regression

Simple correlation

Transformations

Curve fitting

__DIFFERENT ARRANGEMENTS USED IN EXPERIMENTAL DESIGNS__

Factorial Arrangements

Split plot arrangements

Split block arrangements

Split-split plot arrangements

__COMBINING EXPERIMENTS__

Combining experiments across locations

Combining experiments across years

Combining experiments across time and space