Statistics 13, Spring 2011

Overview
In this course, we will present a broad introduction to
some of the fundamental tools and concepts of statistics. Topics include
the representation and interpretation
of data, descriptive statistics and graphical displays,
hypothesis testing, and an introduction to correlation and regression.
We will emphasize quantitative reasoning and
the practice of statistics.

Lectures
Lecture 1: Introduction
(Bills of Mortality, early significance testing,
"a data society?", course themes)
Lecture 2: Reshaping and transforming data
Lecture 3: EDA (basic graphics and extensions)
Lecture 4: Randomized controlled trials, rerandomization tests
Lecture 5 Testing, random number generation
Lecture 6 A/B testing
Lecture 7 Transformations, 2003 recall election
Lecture 8 Four views of probability
Lecture 9 Normality
Lecture 10 The bootstrap (I)
Lecture 11 The bootstrap (II)
Lecture 12 The classics
Lecture 14 Regression (I)
Lecture 15 Regression (II)
Lecture 16 The classics (II)

Homework
Your homework will be a mix of problems from the text as well as
assignments that require using the computer (R). We will avoid having
you do a lot of tedious hand calculations, and instead focus your
"written" output on interpretations.

Labs
Lab assignments are designed around the programming language, R.
You should show up in lab each Thursday, even if you intend
to use your own computer to complete the assignment; this will give the
TA the opportunity to tell you what he expects you to hand in and
for you to ask any questions. Because R runs on almost every computing
platform, you are certainly encouraged to work at home. (Who am I to
stop the "spread" of computing technology?)

Due 4/7:

Introduction

Due 4/14:

EDA Part 1 (4 questions)

Due 4/21:

Rerandomization (4 questions)

Due 5/12:

The bootstrap (3 questions)

Due 5/19:

Confidence intervals

Due 6/2:

Regression




Instructor

Mark Hansen
8951 Mathematical Sciences Building
cocteau@stat.ucla.edu
www.stat.ucla.edu/~cocteau
AIM: cocteautt

Meeting

MW 34:20
1220b Kinsey Pavillion

Office Hours

Th, Fr TBD
8951 Mathematical Sciences

Grading

35%

Takehome Midterms
(4th and 8th weeks)

35%

Labs and Homework

25%

TakeHome Final

5%

Participation



In the calculation of their final grade,
students may substitute their highest Homework and Lab score
for their lowest (nonzero) score.

Computing

Labs and takehome projects will be based on
the R computing environment.
Aside from its strength as a tool for
performing statistical computations and
making graphical displays, we have chosen R because
it is free software and runs on a variety of platforms.
You can obtain a copy of R from the
Comprehensive R Archive Network (select the
socalled "precompiled binary" that matches your
operating system).
In addition, we will be working with R through
RStudio. Download and install the desktop version.

Textbook

Martin Bland
An introduction to medical statistics


