STATISTICS
10
Introduction to Statistical Reasoning
Spring
2001 Syllabus
INSTRUCTOR
Vivian Lew, Ph.D.
Office: 8142D Math Sciences
Phone: (310) 206-6474
Email: vlew@stat.ucla.edu
Mailbox: 8142 Math Sciences Building (usually open from 8:30am to 4:30pm M-F)
Office Hours: Monday 2:00pm - 3:30pm, Tuesday 3:30pm - 5:00pm and by
appointment
TEACHING ASSISTANT |
Office |
Office Hours |
Trudy Poon |
Math Sciences 3969 |
TBD |
MEETING TIMES & PLACES
Lecture Section 1: Mondays, Wednesdays, & Fridays, 8:00am - 8:50am,
Knudsen 1200B
SECTIONS:
ID |
DAY |
TIME |
ROOM |
TA |
DIS 1A 263-031-201 |
Tuesday |
8:00 - 8:50am |
Math Sciences 5203 |
Poon |
DIS 1B 263-031-202 |
Thursday |
8:00 - 8:50am |
Math Sciences 5203 |
Poon |
DIS 1C 263-031-203 |
Thursday |
9:00 - 9:50am |
Math Sciences 5203 |
Poon |
TEXT
Statistics (3rd edition), by David Freedman, Robert Pisani, and Roger
Purves.
SUMMARY
In this course, you
will learn about the role of probability and statistics in describing,
inferring, decision-making, and predicting from data. We will stress the ideas
underlying statistical methods and will focus on applications rather than on
abstract theory. No computer software is used but it is strongly suggested that
you own a calculator with a square root key at minimum for your exams.
SECTIONS and HOMEWORK ASSIGNMENTS
Sections are your
opportunity to work through statistical issues, raise questions, and get a lot
of help from your TA. Your six homework assignments are due at the end of
lecture on the dates listed below.
Homework
assignments are given out during lecture and then posted on the web in case you
miss the handout. Homework is due before the end of lecture on the specified
days/times (last page).
Get help from
people (me, your TA, classmates, friends, tutors) on your homework assignments.
All I ask is that you attempt to solve the problems on your own and please turn
in your own copy. Photocopied assignments will not be accepted (but you may
wish to keep one for yourself).
Only
your best 5 of the 6 assignments will count towards your final grade. Missed/late homework
assignments will not be accepted unless you have made prior arrangements with
me. Please do your homework, it cannot hurt you but only help you. Homework and
labs are graded on the following scale
Homework
and Labs |
Complete
and 100% correct |
Complete
with minor mistakes |
Complete
with major mistakes |
Incomplete
and correct |
Incomplete
with mistakes |
Not
turned in |
Points
Awarded |
6 |
5 |
4 |
2 |
1 |
0 |
Not all homework
questions assigned are graded. Questions are randomly selected for grading.
Therefore, beware of incomplete assignments, they might be worth less than you
think if we select questions for grading that you did not complete. Submit all
homework grading complaints to the professor.
EXAMS
You will have two
midterm exams and a final exam. The final exam code is 1 and it will be given
on Wednesday, 6-13-2001, 3:00PM - 6:00PM in the lecture hall (unless you are
told otherwise later in the quarter). The final exam is cumulative. Always
bring a calculator and your student photo ID or some other kind of photo ID
(e.g. driver's license, passport) to all exams. Identification will be checked
and attendance will be taken. I will provide all answer forms and scratch
paper. You will not need to purchase scantrons or bluebooks for any exam in
this course.
MISSED EXAMS and GRADE APPEALS
Make-up
examinations are given only when circumstances beyond a student's control make
attendance during the scheduled examination period impossible. Documentation
will be required to verify a student's claim and permission to take a make-up
examination must be obtained from the instructor. If a make-up exam is
permitted, it will be written individually for that student and will have a
different format that the regular examination. In all cases, final
determination of whether or not to give a make-up examination rests with the
instructor.
There may be a time when we make a mistake grading one of your exams. If you think this is the case, write a note describing the error, attach it to the original exam, and give it to me within 3 business days of the return of your midterm. I will review your argument and the initial grading decision and return a decision to you in a timely manner.
FINAL GRADE
Your grade is based on
your best 5 of the 6 homework assignments (total 10%), the 2 midterms (20%
midterm 1, 30% midterm 2 -- total 50%) and the final (40%). The course is
usually graded on a "curve". Grades are not e-mailed, posted, or
given out over the phone, they can be found on URSA in a timely manner. If you
believe your final grade is not correct after it has been issued, please
contact me before the end of the second week of the next quarter. Requests for
corrections after that time period will be denied unless it was due to a procedural
or clerical error.
STAT 10 WWW PAGE
Class related material (i.e. lecture notes, handouts, practice exams) is
available to you via the World Wide Web. The URL (``address'') of this course's
page is:
http://www.stat.ucla.edu/courses/stat10_1.php
SCHEDULE OF EVENTS
EVENT |
|
DATE |
Problem Set 1: |
|
Due by the end of lecture April 13 |
Problem Set 2: |
|
Due by the end of lecture April 20 |
Review Session (in lecture): |
|
April 23 |
Midterm I: |
|
April 25 |
Drop Date w/ No Notation |
|
April 27 |
Problem Set 3: |
|
Due by the end of lecture May 4 |
Problem Set 4: |
|
Due by the end of lecture May 11 |
Last Day to change to P/NP |
|
May 11 |
Review Session (in lecture): |
|
May 21 |
Midterm II: |
|
May 23 |
Problem Set 5: |
|
Due by the end of lecture May 25 |
Holiday |
|
May 28 |
Problem Set 6: |
|
Due by the end of lecture June 8 |
Review Sessions (in lecture): |
|
June 6 and 8 |
Final: |
|
Wednesday June 13 -- 3:00pm - 6:00pm |
Quick Overview of Stat10
Statistics is the science of collecting, presenting, and interpreting data to answer questions.
There are four primary issues:
1.Determining the question and the data that will help you answer the question.
2.Collecting the data.
3.Summarizing and presenting the data graphically and numerically.
4.Making generalizations from the data and drawing conclusions. Usually by making comparisons between groups of people, animals, or things.