Top Research Papers on Statistics

Topics • One-sample estimation and hypothesis tests • Two-sample estimation and hypothesis tests • Regression and ANOVA • Generalized linear models Important components of these topics include power, sample size determination, and observable differences for methods based on normality assumptions as well as alternatives to those assumptions. The statistics programming language R will be used heavily in this course. An extension to R called Rstudio also is recommended. Grading Policy Course grade will be based on quizzes, homework projects and the final project. A very useful extension for R is ...

This portfolio prepares for the introduction level undergraduate statistic course (Stat 380) for the students with calculus background, which includes the course goals, contents as well as teaching methods for large session classes. Analysis and evaluation of student learning are also included. In-class activities and discussion helping students’ engagement are introduced. The homework is assigned by Canvas, which summaries the students’ solution and provides analysis for each student.

2 Probability 4 2.1 Set Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Probabilistic Model Discrete Case . . . . . . . . . . . . . . . . . . 5 2.3 Calculating the Probability of an Event The Sample-Point Method . 8 2.4 Tools for Counting Sample Points . . . . . . . . . . . . . . . . . . . 9 2.4.1 Multiplication Principle . . . . . . . . . . . . . . . . . . . . 9 2.4.2 Permutation . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.4.3 Combination . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5 Conditional Probability and Independence . . . . . . ...

This course focuses on modern Applied Statistics with S, 4 Ed, which aims to provide a foundation for future generations of statisticians to use in the field of quantitative medicine.

As Derek Jeter strolls toward the plate, the announcer tosses out a smattering of statistics - from hitting streaks to batting averages. But what do the numbers mean? And how can America's favorite pastime be a model for learning about statistics? "Sandlot Stats" is an innovative textbook that explains the mathematical underpinnings of baseball so that students can understand the world of statistics and probability. Carefully illustrated and filled with exercises and examples, this book teaches the fundamentals of probability and statistics through the feats of baseball legends such as Hank Aa...

The Bayes factor, Bayes’s theorem, Bayesian estimation, and Bayesian probability are cited as well as anecdotal evidence and bias confirmation are investigated.

In 2004, 70% of high school graduates completed either Algebra 2, pre-calculus or calculus as their highest-level math course. (Dossey, 2008) This 70% probably includes all the high-school seniors that go on to college.

The statistical theory for counting extremes is discussed. The statistics of exceedances are nonparametric since the methods require only nominal level data from an underlying continuous distribution. It is assumed the observations are independent and the parameters of the underlying distribution do not change or they change in a known way. (ACR)

Links to free government statistical information that was formerly in the database Stat-USA are shown.

This page considers statistical issues as part of the Caslon Analytics guide to web metrics, internet statistics and online demographics.

During the semester, you may do one book report for extra credit on a book that you choose, and use material from other sources to demonstrate what you learned from the book.

To combat students' fear of statistics I employ my students at a fictional company, Stats Dairy, run by cows. Almost all examples used in the class notes, exercises, humour and exams use data ‘collected’ from this company.

in the penultimate chapter: identify goals, cause-effect analysis, modeling, costbeneŽ t analysis, and recommendations to management. Most chapters end with a checklist like this, and most of those lists (the calculus one being an exception) have a similar character of moving from goals and deŽ nitions, to data collection, to data analysis, to validation, and Ž nally to predictions or business decisions. This is the aspect of the book that I think is quite laudable and sound. It reects the author’sintelligenceandhowhe has usedhis education(PhDin mathematics) and other skills to advance a succe...

Methods and apparatus for controlling the processing of a substrate during a process step that is sensitive to one or more process conditions and an apparatus for processing substrates where the apparatus comprises optimized control parameters are presented.

This HTML-based and flexibly applicable computer tool for supporting teaching and learning statistics in introductory courses via the internet or from a CD allows the user to study statistical methods under varying application conditions or by using different data sets without any additional software overhead.

The computer program STATS is designed to reduce large volumes of daily or monthly data to a few meaningful statistics or curves and provides for the analysis of output from other HEC programs like HEC5.

A selected list of Websites and organizations, both national and international. Includes major providers of North Carolina statistics.

Stats Accelerator helps you algorithmically capture more value from your experiments by reducing the time to statistical significance, so you spend less time waiting for results. It does this by monitoring ongoing experiments and using machine learning to adjust traffic distribution among variations—in other words, it shows more visitors the variations that have a better chance of reaching statistical significance. In the process, it attempts to discover as many significant variations as possible.

In this study, a free Turkish statistical package Selcuk STAT encoded with Delphi is compared with some other common statistical packages SPSS v17 and Minitab v15 in terms of their performance and speed.

This book is written at a lower mathematical level than many other introductory stochastic processes books such as those of Taylor and Karlin (1993) and Resnick (1992) but for the mixed group of students that I was teaching, the level would probably have been appropriate.

Stats Accelerator helps you algorithmically capture more value from your experiments by reducing the time to statistical significance, so you spend less time waiting for results.

The notes and scripts included here are copyrighted by their author, Larry P. Ammann, and are intended for the use of students currently registered for Stat 3355.

Links to free government statistical information that was formerly in the database Stat-USA State of the Nation Reports are shown.

A methodology to perform Statistical Lithography Rules Check (Stat-LRC) involving design yield based on interconnect linewidth distribution for variation in lithographic input error sources is described and yield recovery improvement has been demonstrated.

Students are expected to run R on their own computer or a computer they have plenty of access to and control over and be prepared to do a lot of self-guided learning.

This research guide was designed to introduce you to the field of mathematics. You'll find books, article databases, and other resources you need to start your research.

This paper presents the results of a double-blind ANOVA study on the relationship between Repeated Measures Interactions and Regression Correlation and Covariance Effect Size in the context of Messy Data.

Within Psychology many students reportedly experience statistics anxiety with large proportions failing to make the connection between learning a science subject and conducting and analysing research (Onwuegbuzie & Leech, 2003). The current project employs second and third year psychology students, who have an interest in psychological science research, to provide mentoring to first and second year students in order to enhance levels of support and confidence whilst decreasing anxiety. Mentoring has become increasingly popular in Higher Education as a route to enhancing academic performance an...

Starting out Presenting data Summarising univariate data Summarising bivariate data Assessing risk Putting probability to work Simulating populations Statistical decision making Statistical decision making using bivariate data Managing statistical research

The EM algorithm for an HMM with hidden states zt ∈ {1, . . . , k} and isotropic Gaussian emission probabilities, p(xt|zt), for xt ∈ Rd (d ≥ 1).

Statistical educators should support offering three introductory statistics courses: STAT 100 (Statistical Literacy for non-quantitative majors), STAT 101 (Traditional inferential statistics) and STAT 102 (Social statistics for decision makers). The support for the STAT 102 claim includes the needs of most students taking introductory statistics, the different kinds of decisions being made, the growing importance of big data, the limited amount of free time in the current STAT 101 course, the 2016 update to the GAISE guidelines, the importance of confounding in influencing statistical associat...

This article will focus on a description and evaluation of the program itself, as well as on experiences of teachers and students of this computer program.

A digital simulation tool is developed that can be used for large SFQ circuits with the assumption that the constituting gates have probabilistic, mainly Gaussian, output distributions and also gives the output probabilities for the circuits and individual gates.

In this paper we introduce how to analyze survival data via a SRC-Stat statistical package. This provides classical survival analysis (e

Proceedings of the NODALIDA 2011 Workshop Constraint Grammar Applications are presented, with a focus on constraint grammar applications.

We observe noisy measurements of this function yk = θ(kε) + zk, where (zk)k≤n ∼iid N(0, σ), and are interested in estimating θ with respect to the normalized square loss L(θ̂,θ) = ‖θ̂ − θ‖2/n. We define the discrete derivative by letting ∆θ(kε) = [θ((k + 1)ε)− θ(kε)]/ε for k ∈ {0, . . . , n− 2}, and ∆θ((n− 1)ε) = [θ(0)− θ((n− 1)ε)]/ε (periodic boundary conditions). We consider the following parameter class

This guide explains the library related details for the "What is the mean age of books in the Mardigian Library?" project

Courses in statistics and research methods often included as part of their lab exercises an introduction to mainframe statistical packages such as spss or BMD.

Statistics 2450 is a Data Analysis course in the Quantitative and Logical Skills category of the GE Requirements, where students develop skills in drawing conclusions and critically evaluating results based on data.

This lecture will show the rates of FTRL on the concrete examples the authors discussed earlier to build some intuition, and introduce the entropic regularizer, a useful regularizer when they have to make actions that are probability distributions.

Statistics instructors are increasingly using stand-alone applets to illustrate statistics concepts to students. There are hundreds of applets available on the web, but locating a quality applet to serve a particular purpose can be time consuming. This paper presents the STAT-ATTIC (STATistics Applets for Teaching Topics in Introductory Courses) website, located at http://sapphire.indstate.edu/~stat-attic/index.php, as a tool for locating statistics applets for a particular pedagogical purpose. The site has links, with descriptions, to approximately 600 publicly available applets on topics com...

Information is provided on how to locate test instruments and critiques of measures and how to use software to manage and analyse data.

The statistical techniques that can be used for extreme value analysis of multivariate data are outlined. All the techniques suggested are derived from multivariate statistical procedures, ranging from classic discriminant analysis to modern cluster analysis algorithms. Also presented is an introduction to the Weibull or Fisher Type 3 Extreme Value distribution. This distribution is used in the study of reliability and in materials failure studies. The density and distribution functions are presented along with formulas for several estimable statistics. The Weibull distribution allows the opti...

ABSTRACT The statistics requirement in social work curricula can be seen by students as a detour from the substance of social work. In this note, I describe my experience teaching part-time master’s students that statistical thinking is social work: it is an application of the social work code of ethics and a critical tool in practice for making pragmatic decisions. I use two applied examples to demonstrate how statistical thinking can equip social workers to both identify inequity (through “rejecting the null”) and avoid practices with insufficient evidence (through “failing to reject the nul...

List of Figures and Tables Acknowledgments Preface Chapter One: Basic Concepts Part I: Variables Level of Measurement Dichotomous Variables Operationalized Variables Independent (IV) and Dependent (DV) Variables Causality Units of Analysis: Individual and Place-level Data Part II: Thinking about Procedures Descriptive and Inferential Statistics Difference Observing and Estimating Conclusion Key terms Chapter Two: Describing Distributions Part I: Frequency Distributions Part II: Summary Measures Measures of Central Tendency (Mean, Median, Mode) Measures of Dispersion (or Variability) Categoric ...

The outline of SENSORD/Stat is shown and a prototype of a room temperature monitoring system is shown as a preliminary result of Sensenord/Stat, an extension of sensor-event-driven service coordination middleware that cooperatively works with R, which is an open source statistical computing and graphic environment.

2 Lecture 2: Evaluation of Statistical Procedures I 2 2.1 How to compare δ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Comparing risk function I: Bayes risk . . . . . . . . . . . . . . . . . . . . . . 3 2.3 Bayes theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.4 Bayes risk revisited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

This guide to how to find the data you need for your studies in Health, Business, Psychology, Statistics and other disciplines helps you locate test instruments and critiques of measures.

'Stats Means Business' is an introductory textbook written for Business, Hospitality and Tourism students who take modules on Statistics or Quantitative research methods.Recognising that most users of this book will have limited if any grounding in the subject, this book minimises technical language, provides clear definition of key terms, and gives emphasis to interpretation rather than technique.'Stats Means Business' enables readers to: appreciate the importance of statistical analysis in business, hospitality and tourism understand statistical techniques and develop judgement in the ...

This result partially explains why the MLE, which has the smallest training loss, is also likely to achieve a small testing error when there are enough training examples.