Stat 305
Fall 2013
Intro and Chaps 1-3
Intro
Syllabus - show syllabus.
Introduce myself
Read chapters (before lectures); check homework on Owlspace.
Roadmap of class.
We wish to answer questions and make decisions. How shall I prepare my
lectures? W
Chapter 9b
E. Neely Atkinson
November 9, 2013
In this lab, we look at methods for multiple regression. We also explore some additional
topics in regression analysis.
Multiple regression. The commands for multiple regression are basically the same
as for
Chapter 8
E. Neely Atkinson
October 26, 2013
1. Sign test. The sign test is a simple nonparametric test for paired data. The standard
packages provided with R do not provide a sign test; if you search the web, you can
nd packages that do. However, the sig
Stat 305
Fall 2013
Chapter 16: Survival Analysis
We turn to survival analysis; also known as reliability analysis or time to event analysis.
We have survival times t1 , t2 , . . . , tn . These are typically time from treatment to death,
but can actually b
Stat 305, Fall 2013
Chapter 9
For this assignment we will use a data set downloaded from
http:/orion.math.iastate.edu/burkardt/data/regression/regression.html. It is
an edited version of le x03.txt; I have stored it in Owlspace as bp.txt. It is data on ag
Stat 305, Fall 2013
Chapter 11 - Multiple Regression
R comes with a number of built-in data sets; to see a list of them, type ?data. We are
going to use the data set mtcars. To access this data, type data(mtcars). To learn about
the data set, type ?mtcars
Stat 305, Spring 2013
Assignment 2
Solutions
Remember, I do not have a solutions manual for the book. I may well make mistakes
working these problems.
4.9
a)
P (not A) = P (B or AB or O)
= P (B) + P (AB) + P (O), since they are exclusive
= 0.20 + 0.04 +
Stat 305
Spring 2013
Multiple Regression (Chapter 11)
Also, a few other things
Multiple regression is covered in Chapter of the text; I do not follow the text very closely.
Multiple regression has same concepts, but is much richer. Also, when we understan
Stat 305, Fall 2013
Chapter 16
For this assignment we will use the data set surv.txt, which I have stored on Owlsace.
Your data should look like the following.
> data <- read.csv("surv.txt")
> data
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Introduction to R
E. Neely Atkinson
July 21, 2013
1
Introduction
All computing in this class will be done using the R programming language. No previous
experience with R is assumed; all necessary information will be provided in class and in
the lab.
1. R
Stat 305
Fall 2013
Chapter 9: Association and prediction
Suppose we wish to compare the average blood pressure of men and women. We know
how to do this - t-test or normal test. Suppose we wish to compare the response rate to
a given therapy between men an
Chapter 9
E. Neely Atkinson
November 1, 2013
In this lab, we will looks at the basic facilities provided for linear least square regression
in R First, read in the data set provided on Owlspace.
> data <- read.csv("chap9.txt")
> data
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Stat 305
Fall 2013
Chapter 6b - counting data; continued
We wish to study the relation between exposure and disease for some agent and some
disease. In the population, the joint probabilities are
Exp +
Exp Total
Dis +
0.5
0.3
0.8
Dis 0.1
0.1
0.2
Total
0.6
Stat 305
Fall 2013
Chapter 4 - Statistical Inference
I nd the book a little opaque in parts of this chapter. Ill present the same material,
but in my own fashion.
Population and sample.
population - the collection of individuals about whom we wish to ma
Chapter 4a; Distributions
E. Neely Atkinson
September 6, 2013
In this lab, we study computations related to probability distributions. We will focus
on the normal distribution, although the techniques we learn apply to other distributions
as well.
1
The N
Stat 305
Fall 2013
Chapter 4 continued - Statistical Inference
4.5 - 4.8 and Notes
Sampling Distributions. We are interested in a population. We have a sample.
We draw a sample and compute the mean. If we had drawn a dierent sample, we
would have gotten
Chapter 5: One and Two Sample Inference
E. Neely Atkinson
September 20, 2013
In this lab, we will study R functions useful in testing means and variances, as well as
computing sample sizes.
1
Comparing means
The primary method we will use for comparing me
Chapter 3; Descriptive Statistics
E. Neely Atkinson
August 29, 2013
1
Simple descriptive statistics.
We rst read in a sample data le. Youll need to use the appropriate le name for where
the data are stored on the computer you are using.
> data.in <- "data
Chapter 4b
E. Neely Atkinson
September 13, 2013
In this lab, we explore the Central Limit Theorem. We also study the use of Monte
Carlo techniques to determine the distribution of sampling distributions in situations in
which we cannot determine the distr
Stat 305
Fall 2013
Chapter 6a - counting data
We have examined continuous data - now categorical. The data in this case are counts.
Binomial random variables and the binomial distribution. Suppose we have a
sequence of n trials. each trial has the followi
Chapter 6b
E. Neely Atkinson
October 11, 2013
There are several functions which are useful for the topics covered in second half of
Chapter 6, in particular mcnemar.test and mantelhaen.test. By now, you should be
able to study them on your own, using the
Chapter 6a: Tests of Proportions
E. Neely Atkinson
October 4, 2013
In this lab, we will study R functions for testing proportions.
1
One-sample tests
1.1
Exact
The basic function for exact tests of a single proportion is binom.test. Suppose we ip a
coin 2
Stat 305
Fall 2013
Nonparametric and Distribution Free Methods (Chapter 8)
For large sample sizes, the Central Limit Theorem lets us use the normal distribution for
inference. For small sample sizes, we have had to assume particular parametric distributio