Psych 60 Syllabus(update1)

Psych 60 Syllabus(update1) - 
 PSYCHOLOGY
60
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Unformatted text preview: 
 PSYCHOLOGY
60
 INTRODUCTION
TO
STATISTICS
 SPRING
2010
 
 
 
 
 
 Tuesdays
and
Thursdays,
11:00am
–
12:20pm

 101
Center
Hall

 Instructor:
Julian
L.
Parris
 Email:[email protected] Office:
3340
McGill
Hall
 Office
Hour:
Wednesdays
2:00p
–
4:00p
 Teaching
Assistants
 Email
address,
section
time
and
location
 Ryan
Darby
(Grad
TA)
 Kari
Irwin
(Grad
TA)
 Rachael
Lapidis
(Grad
TA)
 [email protected] [email protected] [email protected] Monday,
11:00
‐
11:50am
 Wednesday
9:00
‐
9:50am
 Friday,
12:00
‐
12:50pm
 McGill
Hall
1350
 McGill
Hall
1350
 HSS
2154
 Anna
Hsu
 Tonia
Leung
 Tony
Choi
 Lily
Lau
 [email protected] [email protected] [email protected] [email protected] Monday,
10:00
‐
10:50am
 Monday,
6:00
‐
6:50pm
 Wednesday,
11:00
‐
11:50a
 Friday,
11:00
‐
11:50am
 McGill
Hall
1350
 HSS
1315

 McGill
Hall
1350
 HSS
1128A
 
 
 
 
 Course
Description:

This
course
is
intended
to
introduce
students
to
the
basic
concepts
of
experimental
 design,
data
collection,
data
analysis
and
statistical
inference.

Topics
include
both
descriptive
and
 inferential
statistics;
we
will
discuss
ways
of
visualizing,
describing,
and
analyzing
data.

The
focus
of
the
 class
will
be
on
developing
statistical
reasoning
skills
and
concepts;
computational
skill
is
secondary.

The
 mathematical
skills
required
to
be
successful
in
the
course
do
not
extend
beyond
high
school
algebra.
 
 
 Course
Website:

http://webct.ucsd.edu

(There
will
be
a
link
to
Psych
60
in
your
course
list
if
enrolled)
 
 
 Required
Materials:
 
 Text:
Essentials
of
Statistics
for
the
Behavioral
Sciences,
7th
Ed.
Gravetter
and
Wallnau.

 (Note:
you
may
also
use
the
6th
edition
of
this
book
as
it
is
substantially
the
same.
The
5th
 edition
is
also
acceptable,
but
earlier
editions
are
less
recommended)
 
 Clicker:
i>clicker.

Available
new
and
used
in
the
university
bookstore
and
online.

 Note:
No
other
model
of
clicker
will
work
in
this
class.


 Clickers:
We
are
using
i>Clickers
for
this
class.
No
other
clickers
will
work
with
this
system.

 
 Clickers
are
a
wonderful
way
for
class
to
be
more
interactive
and
for
you
to
check
your
understanding
 during
lectures.
Each
lecture
there
will
be
several
“check
your
understanding”
questions
where
you
will
 be
able
to
try
out
problems
based
on
the
material
you
have
just
seen.
Clickers
not
only
give
you
the
 opportunity
to
see
if
you
in
fact
get
the
material,
but
they
also
allow
me
to
have
instant
feedback
on
your
 understanding.
If
you’ve
never
used
clickers
in
a
class
before,
don’t
worry!
Leaning
to
use
them
is
easy.

 
 
 You
must
register
your
i>clicker
if
this
is
the
first
time
you’re
using
it.
To
register,
visit:
 
 http://www.iclicker.com/registration/
 

 
 
 Lecture
Slides:

Lecture
slides
will
be
posted
on
the
course
website
each
day
after
class.
You
will
still
 need
to
attend
lecture
in
order
to
understand
the
slides
fully.

You
will
be
tested
on
information
given
in
 lecture
that
will
not
necessarily
be
included
in
the
lecture
slides.

 


 
 Podcasting:
http://podcasts.ucsd.edu/


This
course
will
include
both
an
audio
and
video
podcast
 
 
 Lecture
Attendance:
Attendance
in
this
course
is
essential
for
your
success.

Material
covered
in
class
 will
not
necessarily
be
covered
in
the
course
textbook
and
lecture
slides.

If
you
must
miss
class
it
is
your
 responsibility
to
find
out
what
you
missed
with
regard
to
lecture
notes
and
announcements
by
either
 asking
classmates
or
watching
the
video
podcast.

 
 If
you
miss
 turning
in
an
assignment
or
 taking
an
exam,
you
will
not
be
 able
to
make
it
up.
 In
addition,
participation
points
cannot
be
made
up.
 No
 exceptions
 except
 for
 documented
 medical
 emergencies
 and
 other
 university
approved
exceptions.

 
 
 
 Academic
Dishonesty

 Academic
dishonesty
in
any
form
is
against
University
policy
and
will
NOT
be
tolerated.


 
 Academic
dishonesty
includes,
but
is
not
limited
to:

 ‐ Copying
answers
on
tests

 ‐ Using
prohibited
reference
materials
during
an
exam

 ‐ Turning
in
homework
that
you
have
not
completed
yourself

 ‐ Misrepresenting
a
medical
or
family
emergency
or
other
personal
contingency
in
order
to
delay
a
 scheduled
exam
or
get
extra
time
on
an
assignment

 ‐ Modifying
graded
material
and
then
resubmitting
it
to
“correct
the
error
in
grading”

 
 Acceptable
Actions:

 ‐ Studying
and/or
solving
practice
problems
with
other
students
outside
of
class

 ‐ Sharing
notes
with
other
students
outside
of
exams
 
 
 
 
 Grading:

 
 Experimetrix
(research
participation
credit)
 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 

3%




 
(1%
for
each
hour
of
experiments)
 Class
Participation
 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 

6%





 (0.5%
per
lecture,
up
to
6%
total)
 Homework
 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 

16%



(8
x
2%,
lowest
score
of
9
is
dropped)
 Midterms
 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 

40%



(2
x
20%)

 Final
 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 

35%

 
 
 Experimetrix:

Psychology
is
a
science
based
on
observation
and
experimentation.
Much
of
what
we
 know
about
how
people
think
comes
from
the
participation
of
subjects
in
studies
conducted
at
 universities.

During
this
quarter
you
will
have
the
opportunity
to
see
first‐hand
how
research
is
done.
 3%
of
your
grade
in
this
course
is
based
on
participation
in
experiments
in
the
Psychology
Department,
 1%
for
each
hour
of
participation
(3
hours
max).
Experiments
are
usually
about
an
hour
long,
and
are
on
 a
wide
variety
of
topics.
For
example,
some
ongoing
research
looks
at
how
people
make
decisions
about
 what
vacations
to
take,
whereas
other
research
looks
at
how
the
visual
system
allows
us
to
detect
moving
 objects.
All
research
is
safe
and
has
been
approvedby
the
University’s
human
subjects
review
panel.


 
 Signing
up
for
experiments
is
easy.
Simply
visit
https://experimetrix2.com/ucsd/

There
are
directions
 on
that
page
for
how
to
sign
up
for
and
participate
in
experiments.
If
you
have
any
questions
please
 contact
one
of
the
graduate
TAs.

 
 Alternatively,
individuals
not
wishing
to
participate
in
experiments
in
the
psychology
department
can
opt
 to
write
a
3‐4
page
pager
on
a
topic
of
their
choosing
relating
to
statistics
or
experimental
design.

Paper
 topics
must
be
cleared
with
the
instructor
no
later
than
7th
week,
and
are
due
by
Thursday
of
10th
week.

 
 
 Class
Participation
 
 Class
participation
is
a
vital
component
of
this
course.

We
expect
and
look
forward
to
your
participation.

 Through
class
participation
you
will
further
develop
your
analytical
capacity
to
think
critically
about
 research
and
conclusions
people
make
based
upon
research
that
you
will
experience
in
your
everyday
 lives.
Participation
is
recorded
using
the
class
clickers
for
questions
presented
in
class.
In‐class
 participation
questions
are
not
graded
for
accuracy,
but
only
for
your
response.


 
 
 Each
class
you
attend
and
participate
in
starting
second
week
earns
you
 0.5%,
 totaling
 up
 to
 6%
 for
 the
 quarter.
 There
 are
 16
 lectures
 in
 all
 (starting
with
second
week)
and
you
need
to
attend
and
participate
in
 12
to
earn
the
6%.

This
means
you
can
miss,
without
penalty,
4
classes
 for
whatever
reason.
 
 For
each
class,
you
need
to
answer
at
least
70%
of
the
questions
to
be
 counted
as
being
present.
For
example,
if
during
a
lecture
there
are
10
 questions,
 you
 need
 to
 answer
 at
 least
 7.
 If
 there
 are
 5
 questions,
 you
 need
to
answer
3
(3.5
to
be
exact,
but
in
these
non­integer
cases
we
will
 round
 down).
 
 Questions
 are
 not
 graded
 for
 accuracy
 but
 only
 for
 participation.
 
 

 

 
 Homework
and
Discussion
Sections
 
 Weekly
homework
assignments
will
be
posted
online
by
Thursday
evening
and
will
be
due
at
the
 BEGINNING
of
lecture
Tuesdays.
Graded
homework
can
be
picked
up
in
your
assigned
discussion
 sections.
In
order
to
allow
TAs
with
Wednesday
sections
to
thoughtfully
grade
your
homework,
 individuals
with
Wednesday
sections
will
not
receive
homework
back
the
next
day
but
will
receive
their
 homework
back
the
following
Wednesday.
Individuals
in
all
other
sections
will
be
able
to
pick
up
 homework
in
the
next
section
after
they
turn
it
in.

 
 There
will
be
nine
homework
assignments
in
all.
Late
assignments
will
not
be
accepted.

No
exceptions
 except
for
documented
cases
of
illness
and
other
university
approved
reasons.

Your
lowest
homework
 score
will
be
dropped
allowing
you
one
“grace”
homework
should
you
miss
a
homework
assignment
for
 any
reason.

Scores
on
homework
can
only
be
contested
within
2
weeks
of
the
date
they
are
originally
to
 be
returned.
Do
not
wait
until
the
end
of
the
quarter
to
collect
your
homework.

 
 Discussion
sections
are
optional,
but
attendance
is
highly
encouraged.
The
TAs
for
this
class
are
a wonderful
resource
and
should
be
utilized.

Discussion
sections
provide
a
great
forum
in
which
to
seek
 clarification
on
material
presented
in
class
or
in
the
textbook.
You
are
only
allowed
to
attend
the
section
 in
which
you
are
enrolled,
and
you
can
only
pick
up
your
homework
in
the
section
in
which
you
are
 enrolled.
 

 
 Exams:
The
midterms
and
final
will
be
in‐class
multiple‐choice
and
short
answer
exams.
The
final
exam
 is
cumulative
by
the
very
nature
of
statistics;
you
will
have
to
draw
on
material
learned
prior
to
the
 midterms
in
order
to
answer
questions
on
the
final.
However,
more
of
the
material
tested
on
the
final
will
 come
from
the
second
half
of
the
class.
Midterms
will
focus
more
specifically
on
material
covered
since
 the
previous
exam.
 
 
 Grading
Policy:
Assignments
based
on
participation
and
completion
(such
as
participation
points,
 Experimetrix,
and
homework)
will
contribute
to
your
final
grade
without
curving.
Exams
will
be
 individually
standardized
by
way
of
Z‐scoring,
and
then
redistributed
to
a
common
distribution
(you
will
 learn
in
this
class
what
this
is).
This
process
is
done
in
order
to
make
comparisons
and
combinations
of
 these
scores
statistically
valid
(you
will
learn
in
this
class
why
this
is
necessary).
This
is
curving
in
the
 sense
that
your
score
on
an
exam
depends
on
how
others
in
the
class
perform,
but
this
does
NOT
mean
 that
some
proportion
of
this
class
must
or
will
fail
as
is
true
for
classes
graded
on
a
true
curve.

My
policy
 is
that
if
everyone
does
well,
everyone
should
receive
a
good
grade.
 
 
 Makeup
and
Exam
Policy:
If
you
miss
an
exam,
class,
or
homework
assignment,
you
CANNOT
make
it
 up
later.

Under
special
circumstances
(you
have
a
doctor’s
excuse
for
a
serious
ailment),
we
will
work
 with
you.

This
policy
is
strictly
enforced.

Additionally,
if
you
cannot
make
the
final
exam
time
(11:30‐ 2:30
on
06/08/2010),
you
should
not
take
this
class;
final
exams
will
not
be
given
at
another
time.

 
 Note:
Having
three
exams
in
one
day
is
not
a
special
circumstance.

 Course
Calendar
(subject
to
change)
 
 
 Date
 Topics
 
 Week
1
 3/30
 4/01
 
 Week
2

 4/06
 Visualizing
Data:
Graphs
and
Tables
 Introductions,
Syllabus
and
Class
Organization
 Data
structures,
Notation,
Experimental
Design
 Reading
and
Assignments

 for
this
day
 Read:
Syllabus
 
 Read:
Ch.
1
 Read:
Appendix
A
 ­
Due:
Homework
1
 ­
Have
Clicker
by
today
 ‐
Read:
Ch.
2
 ‐
Read:
Ch.
3,
Ch.
4
 4/08
 
 Describing
Data:
Central
Tendency,
Variability
 Week
3

 4/13
 Variability
Cont.,
Standardized
distributions,
Z‐scores,

 ­
Due:
Homework
2
 ­
Read:
Ch.
4
 ­
Read:
Ch.
5
 ‐
Read:
Ch.
6
 4/15
 
 Probability
 Week
4
 4/20
 4/22
 
 Week
5

 4/27
 4/29
 
 Introduction
to
the
Logic
of
Hypothesis
testing
 Hypothesis
Testing,
cont.,
Error
types,
Z‐tests
 ­
Due:
Homework
4
 ‐
Read:
Ch.
8
 ‐
Read:
Ch.
8
 Midterm
1
 The
Distribution
of
Sample
Means
 ­
Due:
Homework
3
 ‐
Read:
Ch.
7
 
 
 Week
6
 5/04
 5/06
 
 Week
7

 5/11
 5/13
 
 Week
8
 5/18
 5/20
 
 Week
9
 5/25
 5/27
 
 Week
10
 6/01
 6/03
 
 6/08
 
 Introduction
to
Analysis
of
Variance
 Analysis
of
Variance
cont.
 Final
Exam


11:30
–
2:30
 ­
Due:
Homework
9
 ‐
Read:
Ch.
13
 ‐
Read:
Ch.
13
 Correlation,
Linear
equations
and
Regression
 Correlation,
Linear
equations
and
Regression
Cont.
 ‐
Due:
Homework
8
 ‐
Read:
Ch.
15
 ‐
Read:
Ch.
15
 Midterm
2
 Frequency
Data,
Chi
Square
Tests
 ­
Due:
Homework
7
 
 ‐
Read:
Ch.
16
 Related
Samples
t‐test
 Estimation
using
the
t‐statistic
 ­
Due:
Homework
6
 ‐
Read:
Ch.
11
 ­
Read:
Ch.
12
 Introduction
to
the
t‐statistic
 Independent
Samples
t‐test
 ­
Due:
Homework
5
 ‐
Read:
Ch.
9
 ‐
Read:
Ch.
10
 ...
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This note was uploaded on 07/26/2010 for the course PSYC PSYC 60 taught by Professor ? during the Spring '09 term at UCSD.

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