Biometry 122: Introductory Biometrics

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Nov 30, 2013 (3 years and 7 months ago)

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Statistics 404/504
:

Multivariate Statistics
,
fall
2013

Course description:

Explore and model multivariate systems. Matrix algebra, correlation matrices, principal components, common
factors, canonical correlation.

Use and interpret computer
-
assisted analysis. Students in STAT 504 are expected to
carry out an additional project and report findings.
Prerequisite: STAT 108 or STAT 109.


4 semester units.
Weekly: 3 hours of lecture, 2 hours of activity.

Meeting times
and location
:

Lectures:
MWF

9
-
9:50,
BSS 302

Labs
:

T 9:00
-
10
:50
, BSS 313



Professor:


Mark Rizzardi
, Department of Mathematics



Office: BSS 336



Email:
rizzardi
@humboldt.edu





Phone: 826

4951



Web
site:
users.humboldt.edu/rizzardi


Office h
ours:


Initial office hours are
:

Mondays (10:00
-
10:50), Tuesdays (11:00
-
12:50), and Wednesdays (10:00
-
10:50)
.
Visit
http://users.humboldt.edu/rizzardi/hou
rs.html

for current office hours. I am also available

by appointment

and a
drop
-
in basis
.

Phone calls are also welcomed.

Please also take advantage of any extra time during lab sections to
ask
questions.

Also, feel free to ask me questions

immediatel
y

after le
cture or

other times that you find me around
campus.

Text:

Multivariate Statistical Methods: A Primer

by Bryan Manly (Chapman & Hall/CRC, 3
rd

ed., 2005)


Soft
ware:

We will be using the free software R. No prior knowledge is expected. See
www.r
-
project.org

for downloading
and other
information.


This may be of use
:
http://www.kharms.biology.lsu.edu/CrawleyMJ_TheRBook.pdf


Course
objectives
:



The objectives of this course are to present the principles of basic applied multivariate statistical methods and how
to implement them in the R programming environment. This course is applications oriented, using well
-
established
theories
in statistical analysis. Although the field of “multivariate statistics” is very wide, we will use the course
text to guide our selection of material. At the end of the semester

you should be able to understand very basic
linear algebra, recognize multiv
ariate data, use R to perform basic applied multivariate statistical analysis as
covered in the text, program in R, and think logically about interpretation and analysis of real multivariate data.

Grading weights and exam dates
:

Homework
, labs,
quizzes:

55
%

[
STAT
404]
,

45% [STAT505]

(lowest
score

will be dropped)

Exam
s
:


10% (lower score of two exams), 15% (higher score of two exams)


Exam 1:



Tuesday
October 8
(in
-
class and take
-
home)



Exam 2:



Tuesday November 19
(in
-
class and take
-
home)

P
roject
[STAT504]
:

10%

Report and presentation due w
eek 15
.

Final exam:


2
0
%

M
onday, December 16 (8:00
-
9:50am
, in
-
class
)
, take
-
home (week 15)











Determining final grade:


Typically, the traditional 90%, 80%, 70% are used to decide A, B, and C grades.
I do employ the use of pluses and
minuses for grades within 2% of a grade

cut
-
off
.
If a difficult exam results in low overall scores, I may scale
according to the top student’s grade or by other creative measures.
Essentially, an A is earned when you
dem
onstrate a strong understanding of the material, a B is earned when you demonstrate good comprehension, and
a C is earned for moderate comprehension


Homework
, labs,

and quizzes
:



Homework
and labs are

necessary to help yourself understand the course material.
It is important that you put
much effort into understanding the ideas behind your solution rather than just mechanically going through the

2

steps.
Each homework, lab, and quiz will typically be 1
0 points and weighted equally unless otherwise noted.
Q
uizzes will be employed when appropriate and with warning.

Late homework will be accepted until the class’
homework are graded, but at a cost of one point per day
. After the class’ homework assignmen
t is

graded, no
credit will be given.


Academic honesty p
olicy:


Students are responsible for knowing and abiding by the HSU policy regarding academic honesty. Please read

www.humboldt.edu/studentrights/academic_honesty.php
.

You are all
owed to work in small groups on homework
and lab assignments, but the work you turn in must be your own work and accurately reflect your understanding of
the material. I reserve the right to have you confirm your understanding of the work you turned in.


Emergencies:



Please review the evacuation plan for the classroom (posted on the or

ange signs), and review
http://www.humboldt.edu/emergencymgmtprogram/evacuation_procedures.php for information on campus
Emergency Procedures. During an emergency,
information can be found campus conditions at
:
826
-
INFO

or
www.humboldt.edu/emergency


Students with d
isabilities:



Persons who wish to request disability
-
related accommodations should contact the Student Disability Resource
Center in the Learning Commo
ns, Lower Library, 826
-
4678 (voice) or 826
-
5392 (TDD). Some accommodations
may take up to several weeks to arrange.
http://www.humboldt.edu/disability/


Attendance and disruptive behavior:


Students are responsible for knowing policy regarding attendance and disruptive behavior:
http://www.humboldt.edu/studentrights/attendance_behavior.php


Add/Drop policy:


Students are responsible for knowing the University policy, procedures, and schedule

for dropping or adding
classes. http://www.humboldt.edu/~reg/regulations/schedadjust.html

Notice:

Details of this syllabus are subject to change with fair notice.