Annual Report
March 16, 1998 - March 15, 1999
Department of Statistics
University of Florida
Gainesville, FL 32611-8545
June, 1999
Contents
1 Research Activities: March 16, 1998 - March 15, 1999
7
2 Non-Refereed Publications
15
3 Technical Reports
19
4 Gr
Annual Report
March 16, 2001 March 15, 2002
Department of Statistics
University of Florida
Gainesville, FL 32611-8545
June 2002
Phone: 352/392-1941
Fax: 352/392-5175
Web Site: http:/www.stat.u.edu
Cover Graph Description: Overvote percentages for 62 Flori
Logistic Regression
Logistic Regression - Dichotomous Response
variable and numeric and/or categorical
explanatory variable(s)
Goal: Model the probability of a particular as a function
of the predictor variable(s)
Problem: Probabilities are bounded bet
1. Is there a relationship between systolic (top number) and diastolic (bottom number)
blood pressure?
2. Below
Village
Biruwa
Talu
Akkeshi
Helluland
Nidoma
Blonduos
Shinobi
Valais
Takazaki
Colmar
Arcadia
Eden
Pauma
Kiyobico
Bjurholm
Kinsale
Maeva
Nelson
TABLE OF CONTENTS
1.
INTRODUCTION.3
1.1 Background.3
1.2 Statement of the problem.5
1.3 Objective of the study.6
1.3.1 General objective.6
1.3.2 Specific objectives.6
1.4
Research question.6
1.5 Significance of the study.
Solutions of Exercises for Logistic Regression (Chapter 15)
1. a) = 0.02. Since it is positive, we conclude that the curve of P (y = 1) is increasing with x; i.e
the estimated probability of voting for the Republican candidate increases with the voters to
STA 6127: Solutions of Exercises for Chapter 14
2a. Percent with a high school education is not signicant, controlling for the other four predictors.
On its own, it is highly signicant. The other four predictors together explain almost all the variability
STA 6127: Solutions of Exercises for Chap. 13
1a. Use rst equation (ignoring fathers education) to get 11 + 2(1) = 13 for whites and 11 for
nonwhites, for which the dierence = 2. b. See p. 102a of solutions manual.
c. The coecient of Z in the second equat
STA 6127: Solutions of Exercises for ANOVA (Chap. 12)
1. a) Let 1 , 2 , ., 12 be the population mean number of true friends of individuals belonging to the
12 astrological signs. The Null hypothesis is given by H0 : 1 = 2 = . = 12 and the alternative
hypo
STA 6127: Exercises for Multiple Regression (Chap. 11)
1. For students at Walden University, the relationship between Y = college GPA (with range 04.0)
and X1 = high school GPA (range 04.0) and X2 = college board score (range 200800) satises
E (Y ) = 0.20
STA 6127: Solutions of Exercises for Multiple Regression (Chap. 11)
1. The Multiple Regression model is given by: E (Y ) = 0.20 + 0.50x1 + 0.002x2 .
a)(i) The mean college GPA is 0.20 + 0.50(4) + 0.002(800) = 3.8. (ii) 2.3.
b) Fixing x2 at 500, we have th
STA 6127: Exercises for Reviewing Basic Regression
1. Anthropologists often try to reconstruct information using partial human remains at burial sites.
For instance, after nding a femur (thighbone), they may want to predict how tall an individual
was. An
STA 6127: Solutions of Exercises for Reviewing Basic Regression
1. The given prediction equation is: y = 61.4 + 2.4x.
a) The y -intercept is 61.4 and the slope is 2.4.
The slope can be interpreted as follows: For a 1 cm increase in the length of th4e femu
STA 6127 Spring 2008 Exam 1
PRINT Name _
True or False:
If we fit the regression model E(Y) = + 1X1 + 2 X2 then if the least squares estimate b2 (of the parameter 2) is positive, then the partial correlation between Y and X2, controlling for X1 must be p
STA 6127 Exam 2 Topics
1-Way ANOVA with Independent Samples (12.1-12.3)
Analysis of Variance (Sums of Squares, degrees of Freedom, F-tests)
Pairwise Comparisons of Treatment Effects
2-Way ANOVA (12.4,12.5)
Main Effects, Interactions
Analysis of Varian
1-Way Analysis of Variance
Setting:
Comparing g > 2 groups
Numeric (quantitative) response
Independent samples
Notation (computed for each group):
Sample sizes: n1,.,ng (N=n1+.+ng)
Sample means:
n Y +L+ n
Y 1 ,., Y g
Y =
1
1
Sample standard deviat
Multiple Linear Regression
Response Variable: Y
Explanatory Variables: X1,.,Xk
Model (Extension of Simple Regression):
E(Y) = + 1 X1 + + k Xk V(Y) = 2
Partial Regression Coefficients (i): Effect of
increasing Xi by 1 unit, holding all other
predictors
Regression Model Building
Setting: Possibly a large set of predictor variables
(including interactions).
Goal: Fit a parsimonious model that explains
variation in Y with a small set of predictors
Automated Procedures and all possible regressions:
Backw
Analysis of Covariance
Combines linear regression and ANOVA
Can be used to compare g treatments, after
controlling for quantitative factor believed to be
related to response (e.g. pre-treatment score)
Can be used to compare regression equations
among g
STA 6127 Exam 2 Spring 2008
.
1. In a country, the mean annual income for immigrants ( 1) is smaller than for natives
( 2). The mean number of years is smaller for immigrants than for natives, and annual
income is positively related to number of years of
STA 6127 Exam 4
PRINT Name_
Spring 2005
1. A countrys population is growing at a rate of 3% per year. If its population is 1
million people currently, what will its population be in 10 years?
2. A study was conducted to determine what factors correlated w
STA 6127 Exam 3 Spr `05 PRINT Name: _
1. A model is fit relating TEMPerature (Y) to the following 3 potential explanatory
variables: LATitude, ELEvation, and LONgitude. The following table gives
regression coefficients and t-statistics for all possible re
STA 6127 Exam 2 Spring 2005
1. Interaction terms are needed in a Two-way ANOVA model when (circle any correct
answer(s):
a) Each explanatory variable is associated with the response.
b) The difference in means between two categories of one explanatory var
STA 6127 Homework #2/3 Due 2/24/12
1-Way ANOVA Hot Dog Calorie and Sodium Contents
The hot dog data set (hotdog.txt) contains data on n=54 brands of hot dogs, classified by
type: beef, meat, and poultry. The calorie and sodium contents are reported for ea
STA 6127 Spring 2012
Homework 3/4 Due 3/26/12
Analysis of Covariance
Using the cloud seeding data, complete the following problems for all tests use significance level). Fill
in answers on this form, and include computer output.
The variables are: day, tr
STA 6127 Homework 6-7 Due April 11
Part 1: Logistic Regression Sexual Activity among Red Cedars
Multiple logistic regression models were fit to determine whether the presence of sexual activity of
Juniperus Virginiana growing in natural cedar woodland and