THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Microblogging today has become a very popular communication tool among Internet users. Millions of users share opinions on different aspects of life everyday. Therefore microblogging web-sites are rich sources of data for opinion mining and sentiment analysis. Because microblogging has appeared relatively recently, there are a few research works that were devoted to this topic. In our paper, we focus on using Twitter, the most popular microblogging platform, for the task of sentiment analysis. We show how to automatically collect a corpus for sentiment analysis and opinion mining purposes. We perform linguistic analysis of the collected corpus and explain discovered phenomena. Using the corpus, we build a sentiment classifier, that is able to determine positive, negative and neutral sentiments for a document. Experimental evaluations show that our proposed techniques are efficient and performs better than previously proposed methods. In our research, we worked with English, however, the proposed technique can be used with any other language.

/pdf/twitter-as-a-corpus-for-sentiment-analysis-and-opinion-zxo77yicta.pdf

Twitter as a Corpus for Sentiment Analysis and Opinion Mining

INTRODUCTION ..................................................................................................................... 561 ORGANIZING CO CEPTS ..................................................................................................... 564 Primary Hypotheses, Closure, Hierarchical Sets, and Minimal Hypotheses ...................... 564 Families ................................................................................................................................ 565 Type 1 Error Control ............................................................................................................ 566 Power ................................................................................................................................... 567 P-Values and Adjusted P-Values ......................................................................................... 568 Closed Test Procedures ....................................................................................................... 569 METHODS BA ED ON ORDERED P-VALUES ................................................................... 569 Methods Based on the First-Order Bonferroni Inequality .................................................. 569 Methods Based on the Simes Equality ................................................................................. 570 Modifications for Logically Related Hypotheses ................................................................. 571 Methods Controlling the False Discovery Rate ................................................................... 572 COMPARING NORMALLY DISTRIBUTED M ANS ......................................................... 573 OTHER ISSUES ........................................................................................................................ 575 Tests vs Confidence I tervals ............................................................................................... 575 Directional vs Nondirectional Inference ............................................................................. 576 Robustness ............................................................................................................................ 577 Others ........................................................................ ....................................................... 578 CONCLUSION .......................................................................................................................... 580

Multiple Hypothesis Testing

The statistical literature on tests to compare treatments after the analysis of variance is reviewed, and the use of these tests in ecology is examined. Monte Carlo simulations on normal and lognormal data indicate that many of the tests commonly used are inappropriate or inefficient. Particular tests are recommended for unplanned multiple comparisons on the basis of controlling experimentwise type I error rate and providing maximum power. These include tests for parametric and nonparametric cases, equal and unequal sample sizes, homogeneous and heterogeneous variances, non-independent means (repeated measures or adjusted means), and comparing treatments to a control. Formulae and a worked example are provided. The problem of violations of assumptions, especially variance heterogeneity, was investigated using simulations, and particular strategies are recommended. The advantages and use of planned comparisons in ecology are discussed, and the philosophy of hypothesis testing with unplanned multiple comparisons is consid- ered in relation to confidence intervals and statistical estimation.

https://www.fc.up.pt/pessoas/amsantos/support/dayquin1989.pdf

Comparisons of Treatments After an Analysis of Variance in Ecology

OBJECTIVE —This study evaluates the ability of the incretin mimetic exenatide (exendin-4) to improve glycemic control in patients with type 2 diabetes failing to achieve glycemic control with maximally effective metformin doses. RESEARCH DESIGN AND METHODS —A triple-blind, placebo-controlled, 30-week study at 82 U.S. sites was performed with 336 randomized patients. In all, 272 patients completed the study. The intent-to-treat population baseline was 53 ± 10 years with BMI of 34.2 ± 5.9 kg/m 2 and HbA 1c of 8.2 ± 1.1%. After 4 weeks of placebo, subjects self-administered 5 μg exenatide or placebo subcutaneously twice daily for 4 weeks followed by 5 or 10 μg exenatide, or placebo subcutaneously twice daily for 26 weeks. All subjects continued metformin therapy. RESULTS —At week 30, HbA 1c changes from baseline ± SE for each group were −0.78 ± 0.10% (10 μg), −0.40 ± 0.11% (5 μg), and +0.08 ± 0.10% (placebo; intent to treat; adjusted P 1c ≤7% ( P P CONCLUSIONS —Exenatide was generally well tolerated and reduced HbA 1c with no weight gain and no increased incidence of hypoglycemia in patients with type 2 diabetes failing to achieve glycemic control with metformin.

/pdf/effects-of-exenatide-exendin-4-on-glycemic-control-and-4nj0pfbpno.pdf

Effects of Exenatide (Exendin-4) on Glycemic Control and Weight Over 30 Weeks in Metformin-Treated Patients With Type 2 Diabetes

In this paper we present a first general proof of Tukey's (1953) conjecture concerning the extension of the Tukey multiple comparisons procedure to the case of unequal sample sizes, thereby proving that the so-called Tukey-Kramer procedure is conservative in all cases. Also a brief history of the conjecture is given and some extensions and further problems concerning the procedure are discussed.

/pdf/a-proof-of-the-conjecture-that-the-tukey-kramer-multiple-2mzrkikjo2.pdf

A Proof of the Conjecture that the TUKEY-KRAMER Multiple Comparisons Procedure is Conservative

The new edition of Anthony Hayter's book continues in the same student-oriented vein that has made previous editions successful. Because Tony Hayter teaches and conducts research at a premier engineering school, he is in touch with engineers daily and understands their vocabulary. This leads to a clear and more readable writing style that students understand and appreciate. Additionally, because of his intimacy with the professional community, Hayter includes many high-interest examples and datasets that keep students' attention throughout the term. PROBABILITY AND STATISTICS FOR ENGINEERS AND SCIENTISTS employs a flexible approach with regard to the use of computer tools. Because the book is not tied to a particular software package, instructors may choose the program that best suits their needs. However, the book does provide substantial computer output (using MINITAB and other programs) to give students the necessary practice in interpreting output. "Computer Note" sections offer tips for using various software packages to perform analysis of the datasets, which can be downloaded from the website. Through the use of extensive examples and datasets, the book illustrates the importance of statistical data collection and analysis for students in the fields of aerospace, biochemical, civil, electrical, environmental, industrial, mechanical, and textile engineering, as well as for students in physics, chemistry, computing, biology, management, and mathematics.

Probability and statistics for engineers and scientists

In this article an investigation is made of the maximum familywise error rate (MFWER) of Fisher's least significant difference (LSD) test for testing the equality of k population means in a one-way layout. An exact expression for the MFWER is derived (see Theorem 1) for all balanced models and for an unbalanced model with k = 3 populations (Type I models). A close upper bound for the MFWER is derived for all unbalanced models with four or more populations (Type II models). These expressions are used to illustrate that the MFWER may greatly exceed the nominal size α of the LSD test. In addition, a simple modification of the LSD test is proposed to control the MFWER. This modified procedure has MFWER equal to the nominal level α for Type I models and no greater than α for Type II models (Theorem 2) and is, therefore, recommended as an improvement over the LSD test. The key to the analysis is two theorems concerning the ranges of independent normal random variables, which are contained in the Append...

https://www.jstor.org/stable/pdfplus/2289074.pdf

The Maximum Familywise Error Rate of Fisher's Least Significant Difference Test

Many quality control problems are multivariate in character since the quality of a given product or object consists simultaneously of more than one variable. A good multivariate quality control pro...

Identification and Quantification in Multivariate Quality Control Problems

Summary. The evaluation of the cumulative distribution function of a multivariate normal distribution is considered. The multivariate normal distribution can have any positive definite correlation matrix and any mean vector. The approach taken has two stages. In the first stage, it is shown how non-centred orthoscheme probabilities can be evaluated by using a recursive integration method. In the second stage, some ideas of Schlafli and Abrahamson are extended to show that any non-centred orthant probability can be expressed as differences between at most (m- 1)! non-centred orthoscheme probabilities. This approach allows an accurate evaluation of many multivariate normal probabilities which have important applications in statistical practice.

Anthony J. Hayter

Papers

A Proof of the Conjecture that the TUKEY-KRAMER Multiple Comparisons Procedure is Conservative

Probability and statistics for engineers and scientists

The Maximum Familywise Error Rate of Fisher's Least Significant Difference Test

Identification and Quantification in Multivariate Quality Control Problems

The evaluation of general non-centred orthant probabilities