A sufficient condition related to mistaken intuition about adjusted sums-of-squares in linear regression

We consider a misconception common among students of statistics involving "adjusted" and "unadjusted" sums-of-squares. While the presence of misconception has been noted before (e.g. Hamilton (1986)), we argue that it may be related to the language we use in describing the meaning of sums-of-squares. For linear regression with two independent variables, we then present a sufficient condition for SSR( X1 | X2 ) > SSR( X1 ) in terms of the signs of the sample correlations between pairs of predictor and response variables, and note how this sufficient condition may also be related to misconceptions held by some students of statistics. --

A Sufficient Condition Related to Mistaken Intuition about "Adjusted" Sums-of-Squares in Linear Regression

We consider a misconception common among students of statistics involving "adjusted" and "unadjusted" sums-of-squares. While the presence of misconception has been noted before (e.g. Hamilton (1986)), we argue that it may be related to the language we use in describing the meaning of sums-of-squares. For linear regression with two independent variables, we then present a sufficient condition for SSR( X1 | X2 ) > SSR( X1 ) in terms of the signs of the sample correlations between pairs of predictor and response variables, and note how this sufficient condition may also be related to misconceptions held by some students of statistics

An Introduction to Statistical Issues and Methods in Metrology for Physical Science and Engineering

This article provides an overview of the interplay between statistics and measurement. Measurement quality affects inference from data collected and analyzed using statistical methods while appropriate data analysis quantifies the quality of measurements. This article brings material on statistics and measurement together in one place as a resource for practitioners. Both frequentist and Bayesian methods are discussed

An ounce of time, a pound of responsibilities and a ton of weight to lose: An autoethnographic journey of barriers, message adherence and the weight-loss process

This article uses an autoethnographic approach to determine how the intersectionality of identities affects message perceptions about weight loss from the lens of two doctoral students. This autoethnography links our personal experiences with the societal and cultural phenomena of obesity and weight loss, and the rhetoric of messages. We know there is a gap in public relations literature about autoethnography, health communication and intersectionality, and we hope to fill it. We also know health communicators seek more effective ways to reach an increasingly diverse audience; we hope to shed light on the issue. We know that many women want to lose weight and hope our narratives will resonate with them. Finally, we recognize autoethnographic skeptics exist in academia, and we hope our article provides insight into and understanding of the usefulness of autoethnographies in the field of public relations.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Applying Quality Control Charts to the Analysis of Single-Subject Data Sequences

Techniques from the field of quality control can be used to classify the quality of individual samples of physical or cognitive performance. After stable baselines have been established for an individual, deviations in performance can be evaluated using control charts. The effectiveness of this approach in evaluating cognitive performance was tested using databases collected under a variety of risk factors. The sensitivity and specificity characteristics of Shewhart, cumulativesum (CUSUM), and exponentially weighted moving average (EWMA) control charts were determined for a total of 174 trials involving 10 participants and 23 cognitive performance assessment measures. The most effective technique in each case was typically a function of the specific performance measure and the type of performance change being evaluated. Sensitivity and specificity for the best techniques were as high as 100%. This study demonstrated the usefulness of quality control charts as a tool to evaluate individual participant performance over time. Actual or potential applications of this research include readiness-to-perform screening of industrial workers in order to improve the health and safety of the workforce.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Imagining the Lives of Others: Empathy in Public Relations

This paper asks how we might theorise empathy in public relations (PR) in the light of a widespread ‘turn’ towards emotion in the academy, as well as in popular discourse. Two distinct notions of empathy are explored: ‘true’empathy as discussed in intercultural communication, is driven by a human concern for the other in order to understand experiences, feelings and situations that may be different from our own; whereas ‘instrumental’ empathy, reflecting a self orientation, is said to characterise much neoliberal market discourse in which corporations are urged to understand their customers better. Thus, while empathy may seem highly desirable as a means to enter into dialogue with an organisation’s publics, particularly during times of social upheaval and crisis, it is important to pay attention to empathy in public relations discourses including whose goals are served by empathetic engagement; and the type(s) of empathy called upon within a PR context. A literature review identified a socio-cultural definition of empathy as ‘imaginary effort’. A review of the public relations literature, however, found that while empathy is considered an important principle and personal attribute, notions of empathy, with a few exceptions, are under-explored. Nonfunctionalist, socio-cultural research which examines the meanings that practitioners associate with empathy is distinctly lacking; therefore in order to gain further insight into empathy, two sources of data were explored. The analysis of a popular online practitioner blog showed that other-centred empathic skill is discursively framed as instrumental in achieving clients’ business objectives. The analysis of three empathy statements drawn from 12 in-depth interviews with practitioners revealed complex empathic discourse in practitioner-client relationships. While the findings are limited to illustrative analyses only, this paper challenges researchers to develop conceptualisations and perspectives of empathy as imaginary effort in public relations

Statistical Modeling of Single Target Cell Encapsulation

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.Wallace H. Coulter Foundation (Young Investigator in Bioengineering Award)National Institutes of Health (U.S.) (Grant R01AI081534)National Institutes of Health (U.S.) (Grant R21AI087107

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology