Steele, Brian - Department of Mathematical Sciences, University of Montana

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Steele, Brian - Department of Mathematical Sciences, University of Montana

The University of Montana Department of Mathematical Sciences Technical Report # 1/2004
Collapsing Heat Waves William R. Derrick and Leonid V. Kalachev
Statistical Assessment of Departure from Historical Conditions1 Brian Steele and Swarna Reddy
Exact Bagging of k-Nearest Neighbor Brian Steele and Dave Patterson
Toward Estimation of Map Accuracy Without a Probability Test Sample
STAT 457 Fall, 2009 Statistics Lab #14: SPSS--ChiSquare ( 2
AN ANALYSIS OF METHODS FOR WAVEFRONT RECONSTRUCTION FROM GRADIENT
Testing a Subset of Regression Coefficients in GLMs (12.5) Recall that the general form of a general linear model (GLM) is given by
A [Statistical] Introduction To "R" From a Lab Assistant's
A VARIATIONAL APPROACH TO VIDEO SEGMENTATION FOR BOTANICAL DATA
Commentary on Chapter 14 Mathematics Achievement and Gender
Spring 2010 Data Analysis III: Displaying Quantitative Data First, a review of the main points of examining categorical data
Land Cover Mapping Using Combination Classifiers BRIAN M. STEELE"
1. Introduction to SPSS for Windows SPSS (Version 17) is a statistical software package available in many of the campus computer
Spring 2010 Data Analysis IV: Describing Distributions Numerically This handout introduces three numerical summaries for quantitative variables as well as one
STAT 216 Introduction to Statistics Fall, 2010 Course Coordinator & Instructor: Cindy Leary Math 002
LAB # 8 STAT 458 Statistical Methods (Continuation), Spring 2010
Math 543: Midterm/Homework 5. Due Wednesday March 12 Analyze the global tuberculosis data set (GlobalTB.txt extracted from http://www.who.int/globalatlas/).
Maximum Posterior Probability Estimators of Map Brian M. Steele
Chapter 4. Probability Probability is a branch of mathematics which addresses uncertainty. As
Fitting Linear Models Description
276 Chapter 7 The Fourier Transform and its Applications Solutions to Exercises 7.2
CALCULUS II -M(ath) 172 Sec. 02 Fall 2010 (4 cr.) Instructor: Demitri Plessas Course Coordinator: Dr. Jennifer Halfpap
5. Inference for Population Means 5.1 Inference for the mean of a population using the t distribution
Tools Used in Lab 25 Chemical Oscillator
Multiple Comparisons (Chapter 9) This handout introduces the notion of multiple comparisons in an ANOVA context, defines
WAVEFRONT RECONSTRUCTION METHODS FOR ADAPTIVE OPTICS SYSTEMS ON GROUND-BASED TELESCOPES
STAT 457 Fall, 2010 Lab #2 2 way tables done by StatCrunch
Symbols and Mediation in Mathematics Luis Moreno-Armella and Bharath Sriraman
An investigation into the use of maximum posterior probability estimates for assessing the accuracy of large maps
Optimal experimental protocol for identification of dissolution and kinetics
Pre-print of Chapter to appear in L.V. Shavinina (Ed). The International Handbook of Giftedness. Springer Science
WATTS THEOREM FOR SCHEMES: PRELIMINARY VERSION A. NYMAN AND S. P. SMITH
Nonparametric Methods for Unbalanced Multivariate Data
Chapter 7: Classroom Practice: Challenging Mathematics Classroom Practices 26 December 2007
On the Identit(ies) of Mathematics Education Bharath Sriraman1
MTL SHORT REPORT The Modeling Perspective in the teaching and learning of mathematical
The Second Edition of The Handbook of International Research in Mathematics Education continues the mission of bringing together important new mathematics education research that
The Montana Mathematics Monograph 4
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS Int. J. Numer. Meth. Fluids 2008; 15:1 Prepared using fldauth.cls [Version: 2002/09/18 v1.01]
Aesthetics and Creativity: An exploration of the relationships between the constructs
Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation
Interdisciplinarity, Creativity, and Learning, pages 1329 Copyright 2009 by Information Age Publishing
Politicizing Mathematics Education: Has Politics gone too far? Or not far enough?
March 2, 2010 15:52 Inverse Problems in Science and Engineering manuscript Inverse Problems in Science and Engineering
Understanding a Teacher's Actions in the Classroom by Applying Schoenfeld's
Mathematics Education Research in Denmark: A Brief Introduction Bettina Dahl, Aarhus University
Reduced model of neurotransmitter transport in the presence of generic receptors and transporters
A Morphology of Teacher Discourse in the Mathematics Classroom Libby Knott
2006 International Conference in Honor of Jacqueline Fleckinger. Electronic Journal of Differential Equations, Conference 16, 2007, pp. 155184.
ERRATA FOR THE OTT/LONGNECKER BOOK AN INTRODUCTION TO
Model Diagnostics The term "model diagnostics"refers to methodology for examining whether or not there are
Examining Lack of Fit in Regression (11.5) In this handout, several visual ways of assessing lack of fit in a regression model are presented
5. Inference for Population Means 5.1 Inference for the mean of a population using the t distribution
Tools Used in Lab 23 Saddle-Node Bifurcation
Graphing Differential Tools Used in Lab 2
Simple Random Sampling (Chapter 2) Simple random sampling (SRS) is a sampling design where n units are selected (without
Department of Mathematical Sciences Fall 2010, Math 582
Fall 2010: M311 (3 cr.) + Lab M317 (1 cr.) Ordinary Differential Equations and Systems
ADMISSIONS APPLICATION FORM 1. Name _____________________________________________________________________________________________
ACCEPTED Book Proposal Shaping the Future of Mathematics Education
Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems
Reduction and identification of dynamic models. Simple example: generic receptor model.
How to Compare Small Multivariate Samples Using Nonparametric Tests
Statistical Assessment of Departure from Historical Conditions1 Brian Steele and Swarna Reddy
Submitted to Environmental and Ecological Statistics A Methodology for Assessing Departure of Current Plant Communities from Historical
MATH 444 Statistical Methods Autumn 2006 Instructor: Brian Steele
MATH 447 Computer Data Analysis Autumn 2006 Instructor: Brian Steele
Data Files for the homework problems can be downloaded from the website http://www.duxbury.com/cgi-
Homework Due Friday, October 27: p. 207: 5.21
Homework Due November 27 (Monday) p. 284: 6.10, 6.14
Final Review problems (solutions available): 6.9, 6.12, 6.20, 6.27, 6.29, Final Review problems (solutions not available yet): 10.18, 10.34, 10.35,
Syllabus for Math 549, Applied Sampling, Autumn 2004 Instructor: Brian Steele, Math 205B, 243-5396, steele@mso.umt.edu
Math 543: Homework for Thursday May 8 Earthquake data These data are measurements recorded at seisometer locations for 23 large earth-
An Application of Bootstrapping in Regression To finish off our discussion of regression methods, I thought I would show an application
Tracing Students' Modeling Processes in School Nicholas Mousoulides, M. Pittalis, C. Christou, and Bharath Sriraman
Introduction to R R is available as a free download from www.r-project.org for Unix, Windows and Mac. It is essentially a
Some Multiple Comparison Procedures (9.4-9.9) We have seen that for ANOVA models with t treatments, we can define a set of t-1 orthog-
Hierarchical regularization for edge-preserving reconstruction of PET images
STAT 421 Probability Theory Fall 2010, MWF 10:10-11:00, Math 211
ZDM 2006 Vol. 38 (Steiner Special Issue) Analyses The Steiner TME-program of 1987
M 524: Linear Algebra with an Introduction to Quadratic Forms Fall 2010 Instructor: Kelly McKinnie Time: MWF 2:10-3:00
A Two Stage Model for Quantitative PCR Emily Stone and John Goldes
Model Formulae Description
3. Looking at Data: Relationships This chapter describes methods for examining the relationship between two quantitative variables or two
Name: Exam I Show all your work
Experimental Designs (15.1-15.3) This handout focuses on two of the simplest types of experimental designs, known as the
On the internal structure of goals and beliefs Gnter Trner, University of Duisburg-Essen (Germany)
An Empirical Investigation of Sixth grade Students' Modelling Processes in Cyprus Nicholas Mousoulides *, Bharath Sriraman **, Constantinos Christou*
Logistic Regression Logistic regression is an example of a large class of regression models
Tools Used in Lab 24 Spruce Budworm
SELECTED ANSWERS Chapter 1: What Is Statistics
Recommended Problem Solutions -Chapter 2 1. Problem 2-1: Voters: The response is a categorical variable.
Homework Due Dec. 4 p. 313: 6.28, 6.36
Children's geometrical strategies-1 -PRE-PRINT OF PAPER TO APPEAR IN NORDIC STUDIES IN MATHEMATICS
Analysis of Variance (ANOVA) (8.1-8.2) Much of statistical inference centers around the ability to distinguish between two or more
-In press at Information Age Publishing, Charlotte, NC-Interdisciplinarity for the 21st Century
Department of Mathematical Sciences DATE: January 26, 2010
The Utility and General Definition of Correlation Coefficients Rudy A. Gideon
R Computer Lab Tutorial--Initial Experience [Revision 0] First done on 2/3/10 in MA 306
Inference -Simple Linear Regression (11.3, 11.4) Recall the example comparing height (y) and armspan (x) measurements for the 18 women
[Pre-print of paper to appear in vol.11, no.1 of The International Journal for Technology in Mathematics Education]
springer.comABCD Advances in Mathematics
An Efficient Estimation Scheme for Phase-Diversity Time Series Data
Using R for Linear Regression In the following handout words and symbols in bold are R functions and words and
Ideal Bootstrap Estimation of Expected Prediction Error for -Nearest5 Neighbor Classifiers: Applications for Classification and Error Assessment
Chapter 10 Problems 10.18. a) = 35/800 = 0.04375. Note n = 35 > 5 and n(1 -) = 800 -35 > 5. Hence,
A Regression Strategy for Analyzing Environmental Data Generated by Spatio-Temporal Processes
Class Notes Class Notes are available at: http://www.math.umt.edu/steele/Math444
ORIGINAL ARTICLE The characteristics of mathematical creativity
STAT216 -Test #1 Name (print): Lab Section: This is a PRACTICE EXAM -I will not be mimicking these problems for the real exam, but this is a rep-
Critical Issues in Mathematics Education, pages ixxvi Copyright 2009 by Information Age Publishing
Inverse Problems in Science and Engineering Vol. 00, No. 00, December 2006, 117
STAT 457 Fall, 2010 Lab #1 Introduction to Lab
Spring 2010: M514 (3 cr.) Topics in Applied Mathematics
Lab # 3 STAT 458 Statistical Methods (Continuation), Spring, 2010
Inference in Multiple Regression w/Example (12.3, 12.4) The purpose of this handout is to consider modeling some data with a multiple linear regres-
M 151 (Precalculus) Spring 2011 Course Coordinator: Regina Souza Instructor Section MTWF Room Office Phone Email
Gender and Strategy Use in Proportional Situations: An Icelandic Study Olof Bjorg Steinthorsdottir & Bharath Sriraman
Pre-print (German version) of ongoing work with Gnter Trner A shorter English version appeared as
Tracing students' Modelling processes in elementary and secondary N. Mousoulides*, B. Sriraman**, M. Pittalis*, & C. Christou*
Interchange, Vol. 39/1, -, 2008. Springer 2006 A Critique and Response to
Lab # 13 STAT 458--Statistical Methods Lab, Spring, 2010
Lab # 7 STAT 458 Statistical Methods (Continuation), Spring, 2010
Lab # 1 STAT 458 Statistical Methods (Continuation), Spring, 2010
Nonlinear Regression Models (13.3) Recall that a parametric model is said to be linear if it is a linear function of the model
WHAT YOU NEED TO KNOW -Test #1 -Chapters 11-12.7 1. Understand the difference between response and explanatory variables, and be able to
Multiple Regression Diagnostics (Chapter 13) In practice, there is much more to regression than merely fitting a model, looking at
8th Annual MATH Film Festival in celebration of Math Awareness Month
[Pre-print of Paper to appear in Nordic Studies in Mathematics Education, vol15, Commentary on
ATTENTION STUDENTS REGISTERED FOR THE APRIL 10th For information about preparing for and taking the WPA, go to www.umt.edu/udwpa .
ADMISSION APPLICATION FORM 1. Name______________________________________________________________________________________________
Technol Aca UC UC NR NR Crs Reg Tui Bldg Fees Equip Activity Camp Health Recy Fac OP Ren Trans Res Bldg Tui NR
M 121 (College Algebra) Spring 2011 Course Coordinator: Regina Souza Instructor Section MWF Room Office Phone Email
M 122 (College Trigonometry) Spring 2011 Course Coordinator: Regina Souza Instructor Section MWF Room Office Phone Email
Chapter 2 Notes (Data) Recall we defined data as numbers or characteristics with some
Recommended Problem Solutions -Chapter 3 1. Problem 3-13: Causes of death
Experimental Design Odds and Ends A 3-Way Factorial ANOVA Example : Continuing with the example relating the factors
WHAT YOU NEED TO KNOW -Test #1: Chapters 1-8 (part of 8) 1. Know the two basic types of variables (quantitative, categorical) and be able to identify which type a
STAT216 -Practice Exam #1 Solutions 1. In left-skewed distributions, the mean is most typically smaller than the median .
Introduction to Probability and Statistics -STAT 341 Spring 2011 Instructor: John Hossler, Corbin 269, 243-5538, jzhoss@mso.umt.edu
D. Patterson 9/1/2010 Introduction to R
Counting and Probability Problems 1. How many ways can 6 kids line up at a drinking fountain?
STAT 457 (1 credit) Statistical Methods Lab, Fall, 2010 Instructor: Michael O'Lear m.olear@mso.umt.edu
Lab Reports and Class Procedure Our normal lab procedure will consist of the following
Examining the ANOVA Variance Homogeneity Assumption (7.4, 8.4) In ANOVA problems, variance homogeneity refers to having equal population variances for
STAT 457 Fall, 2010 Lab #3 Creating graphs and tables of quantitative variables in StatCrunch
1 August 30, 2010, Jeff Johnson Summary 1. Today we covered some basic definitions and important underlying questions
Stat 549 Applied Sampling -Overview The intent of this handout is to provide a brief overview to some of the topics in applied
Examples of Sampling Problems For the following situations, identify the population, the sampling units, and the sampling
Sample Size Considerations (Chapter 4) Up to now, we have assumed that the sample size n was known, and have studied properties
Unequal Probability Sampling (Chapter 6) Unequal probability sampling is when some units in the population have probabilities of
STAT 341 Probability and Statistics Spring 2010, MWF 10:10-11:00, Math 211
Stat 341 Spring 2010 Data Analysis I Statistics is...
Spring 2010 Data Analysis II: Displaying and describing categorical data This handout is the first of several in which we look at ways of exploring and describing the patterns in
Tools Used in Lab 3 Growth and Decay
Some Other Experimental Designs In addition to the completely randomized design (CRD), randomized block design (RBD),
2. Examining Distributions This chapter describes procedures for examining categorical and quantitative variables
6. Inference for Two-Way Tables This chapter introduces a method for analyzing the relationship between two categorical
Tests for Categorical Data (10.4-10.6) This handout focuses primarily on two methods of inference for categorical data, as well as
The Simple Linear Regression Model (11.1, 11.2) Often, we have two variables and believe that one affects or explains the other (e.g.: smoking
Introduction to Multiple Linear Regression (12.1-12.3) The general form of a multiple linear regression model, known as the general linear
The Factorial Design (15.5) This handout introduces the Factorial Design, the purpose of such a design, model form,
Comparing the Slopes of Several Regression Lines (12.7) Suppose we are interested in developing a simple linear regression model to explain some
Logistic Regression -An Overview (12.8) Logistic regression models are regression models for binary response variables. To see when
WHAT YOU NEED TO KNOW -Chapters 12.8, 13, 8 1. Refresh your knowledge from the review sheet for the first exam.
WHAT YOU NEED TO KNOW -Final Weeks 1. Be able to interpret all tests and confidence intervals in the language of the problem.
A Mathematics Puzzle This is a State-Level MathCounts puzzle. There are 20 problems given on the following
STAT 458 Statistical Methods Lab (Continuation), Spring of instructor: Mike O'Lear email: m.olear@mso.umt.edu
Brief Introduction To SPSS [1] Creating data
1. Introduction to SPSS for Windows SPSS (Version 16) is a statistical software package available in many of the campus computer
2. Examining Distributions This chapter describes procedures for examining categorical and quantitative variables
4. Sampling distributions 4.1 Selecting a random sample of cases
6. Inference for Two-Way Tables This chapter introduces a method for analyzing the relationship between two categorical
R Data Import/Export Version 2.7.2 (2008-08-25)
Lab # 4 STAT 458 Statistical Methods (Continuation), Spring, 2010
Lab #9 Report STAT 448--Statistical Methods, Spring, 2010
Queries from the MA 447 class in 2008, in response to the following question: After Using R-Commander for a while, how do you like it?
Lab # 12 STAT 458--Statistical Methods Lab, Spring, 2010
3. Looking at Data: Relationships This chapter describes methods for examining the relationship between two quantitative variables or two
Lab # 5 STAT 458 Statistical Methods (Continuation), Spring, 2010
An Introduction to R Notes on R: A Programming Environment for Data Analysis and Graphics
A NONNEGATIVELY CONSTRAINED ITERATIVE METHOD WITH STATISTICALLY BASED STOPPING RULES
New Book Series SENSE PUBLISHERS, THE NETHERLANDS
PRE-PRINT OF PAPER SUBMITTED TO EDUCATIONAL STUDIES IN MATHEMATICS Conjecturing via reconceived classical analogy
ORIGINAL ARTICLE A brief history of mathematics education in Turkey
Mathematics Education in Iceland: Explaining the Non-homogeneity in a Homogenous System
Re-conceptualizing Mathematics Education as a Design Science
Surveying Theories and Philosophies of Mathematics Education
Prediction of river hydraulic conditions via satellite multi-spectral imagery and statistical learners
SOME VIRTUALLY SPECIAL HYPERBOLIC 3-MANIFOLD ERIC CHESEBRO, JASON DEBLOIS, AND HENRY WILTON
DISTINGUISHING DIVISION ALGEBRAS BY FINITE SPLITTING DANIEL KRASHEN AND KELLY MCKINNIE
Preface to Chapter 2 Ernest's Reflections on Theories of Learning Lakatos-Hersh-Ernest: Triangulating Philosophy-Mathematics-Mathematics Education
Commentary on Chapter 11 On Proof and Certainty-Some Educational Implications
Critical Issues in Mathematics Education, pages 319336 Copyright 2009 by Information Age Publishing
advances in mathematics education ISBN 978-1-848-00000-0
PME-NA-Atlanta Working Group Research Advances in Theories of Mathematics Education
MATHEMATICAL BIOSCIENCES http://www.mbejournal.org/ AND ENGINEERING
advances in mathematics education ISBN 978-1-848-00000-0
Let Lakatos Be! -A Commentary to "Would the real Lakatos please stand up" Bharath Sriraman
c de Gruyter 2007 J. Inv. Ill-Posed Problems 15 (2007), 128 DOI 10.1515 / JIP.2007.002
Exact bootstrap k-nearest neighbor learners Brian M. Steele, Dept. of Mathematical Sciences, University of Montana, Missoula
The Montana Mathematics 2007 Monograph 3
TRACING STUDENTS' MODELING PROCESSES IN SCHOOL
BIT Numerical Mathematics (2006)46:000-000 c Springer 2006. DOI:10.1007/s10543-000-0000-x
Magic squares and antimagic graphs P. Mark Kayll
A note on the null distributions of some test statistics for profile analysis under general conditions
Reduced models of algae growth Heikki Haario,
ON CERTAIN CONTROL PROBLEMS FOR A CLASS OF SINGULARLY PERTURBED PARABOLIC EQUATIONS
The Mathematics of Estimation: Possibilities for Interdisciplinary Pedagogy and Social Consciousness
[PRE-PRINT OF REVIEW TO APPEAR IN: EDUCATIONAL STUDIES IN MATHEMATICS, 2010 ]
Proportional reasoning developmental trajectories of Icelandic girls Icelandic 5th
From Problem Solving to Modelling-A meta-analysis Nicholas Mousoulides1
Astronomy & Astrophysics manuscript no. nonneg c ESO 2006 April 18, 2006
Analyses ZDM 2005 Vol. 37 () Structural Stability and Dynamic
Analyses ZDM 2005 Vol. 37 (3) An Empirical Taxonomy of
Introduction to R for STAT 549 D. Patterson, September 2010
Lab # 2 STAT 458 Statistical Methods (Continuation), Spring, 2010 Introduction To Chi-Squared in R and to Simple Linear Regression in SPSS
The Montana Mathematics Monograph 2
Lab # 11 STAT 458--Statistical Methods Lab, Spring, 2010
MOVING FORWARD IN INTERNATIONAL MATHEMATICS EDUCATION RESEARCH Lyn D. English
4. Sampling distributions 4.1 Selecting a random sample of cases
Asymptotics for Tests on Mean Profiles, Additional Information and Dimensionality under Non-normality
SINGULARLY PERTURBED PERIODIC PARABOLIC EQUATIONS WITH ALTERNATING BOUNDARY LAYER TYPE SOLUTIONS IN
Volume 41 Issues 12 January 2009 ZDM|Volume41Issues12January2009pp125611858
INTRODUCTION TO SAMPLING This handout provides a brief overview of some of the main ideas in applied sampling.
Chapter 1: Introduction Statistical studies may be roughly divided according to the possible scope of inference as
Chapter 3 Examining Data This chapter discusses methods of displaying quantitative data with the objective of under-
Chapter 2: Regression analysis This chapter introduces a method of analyzing the relationship between one quantitative