Analysis of the Relationship between Types of Rebuttal, Interaction Patterns and Informal Statistical Inference in the Students' Discussion on Comparing the Data of Two Groups

2018 ◽  
Vol 28 (1) ◽  
pp. 113-139
Author(s):  
Minju Seo ◽  
Yunjoo Yoo
Keyword(s):  
Statistical Inference ◽  
Interaction Patterns ◽  
Informal Statistical Inference ◽  
The Relationship

Learning Language Levels in Students Accurate with a History Academic Achievement History

2017 ◽  
Vol 1 (2) ◽  
pp. 137
Author(s):  
Noorlela Binti Noordin ◽  
Abdul Razaq Ahmad ◽  
Anuar Ahmad
Keyword(s):  
Academic Achievement ◽  
Statistical Inference ◽  
Quantitative Data ◽  
Quantitative Methods ◽  
Descriptive Statistics ◽  
Language Test ◽  
The Subject ◽  
The Difference ◽  
Learning Language ◽  
The Relationship

This study was aimed to evaluate the Malay proficiency among students in Form Two especially non-Malay students and its relationship to academic achievement History. To achieve the purpose of the study there are two objectives, the first is to look at the difference between mean of Malay Language test influences min of academic achievement of History subject among non-Malay students in Form Two and the second is the relationship between the level of Malay proficiency and their academic achievement for History. This study used quantitative methods, which involved 100 people of Form Two non-Malay students in one of the schools in Klang, Selangor. This study used quantitative data were analyzed using descriptive statistics and statistical inference with IBM SPSS Statistics v22 software. This study found that there was a relationship between the proficiency of Malay language among non-Malay students with achievements in the subject of History. The implications of this study are discussed in this article.

Infodemics on Youtube: Reliability of Content and Echo Chambers on COVID-19 (Preprint)

2021 ◽  
Author(s):  
Niccolò Di Marco ◽  
Matteo Cinelli ◽  
Walter Quattrociocchi
Keyword(s):  
Information Diffusion ◽  
Two Dimensions ◽  
World Health ◽  
Interaction Patterns ◽  
Political Preference ◽  
Political Bias ◽  
Echo Chambers ◽  
Echo Chamber ◽  
Health Organization ◽  
The Relationship

UNSTRUCTURED Social media radically changed how information is consumed and reported and elicited a disintermediated access to an unprecedented amount of content. The world health organization (WHO) coined the term infodemics to identify the information overabundance during an epidemic. Indeed, the spread of inaccurate and misleading information may alter behaviours and complicate crisis management and health responses. This paper addresses information diffusion during the COVID-19 pandemic period with a massive data analysis on YouTube. First, we analyze more than 2M users’ engagement in 13000 videos released by 68 different YouTube channels, with different political bias and fact-checking indexes. We then investigate the relationship between each user’s political preference and her/his consumption of questionable/reliable information. Our results, quantified using information theory measures, provide evidence for the existence of echo chambers across two dimensions represented by the political bias and by the trustworthiness of information channels. Finally, we observe that the echo chamber structure cannot be reproduced after properly randomizing the users’ interaction patterns.

Recovering Business Process Models with Process Patterns

2013 ◽  
pp. 223-249
Author(s):  
Vitus S. W. Lam
Keyword(s):  
Business Process ◽  
Process Management ◽  
Control Flow ◽  
Process Models ◽  
Interaction Patterns ◽  
Workflow Patterns ◽  
Business Process Models ◽  
The Core ◽  
Forward Engineering ◽  
The Relationship

Originating from a pragmatic need to document strategies for modelling recurrent business scenarios, collections of workflow patterns have been proposed in the business process management community. The concrete applications of these workflow patterns in forward engineering have been extensively explored. Conversely, the core concern of business process archaeology is on recovering business process models from legacy systems utilizing reverse engineering methods. Little attention is given to the relationship between business process recovery and workflow patterns. This chapter aims to give a compact introduction to workflow control-flow patterns, workflow data patterns, workflow exception patterns, and service interaction patterns. In particular, the feasibility of combining workflow patterns with business process archaeology is examined by drawing on the research results of the MARBLE framework.

scholarly journals Mastering Panel Metrics: Causal Impact of Democracy on Growth

2019 ◽  
Vol 109 ◽  
pp. 77-82 ◽  
Author(s):  
Shuowen Chen ◽  
Victor Chernozhukov ◽  
Iván Fernández-Val
Keyword(s):  
Panel Data ◽  
Statistical Inference ◽  
Fixed Effects ◽  
State Of The Art ◽  
Panel Data Analysis ◽  
High Dimensional ◽  
Econometric Methods ◽  
Long Run ◽  
Causal Impact ◽  
The Relationship

We revisit the panel data analysis of Acemoglu et al. (forthcoming) on the relationship between democracy and economic growth using state-of-the-art econometric methods. We argue that panel data settings are high-dimensional, resulting in estimators to be biased to a degree that invalidates statistical inference. We remove these biases by using simple analytical and sample-splitting methods, and thereby restore valid statistical inference. We find that debiased fixed effects and Arellano-Bond estimators produce higher estimates of the long-run effect of democracy on growth, providing even stronger support for the key hypothesis of Acemoglu et al.

scholarly journals Repeated sampling with a black box to make informal statistical inference accessible

2019 ◽  
Vol 22 (2) ◽  
pp. 116-138
Author(s):  
Marianne van Dijke-Droogers ◽  
Paul Drijvers ◽  
Arthur Bakker
Keyword(s):  
Statistical Inference ◽  
Black Box ◽  
Informal Statistical Inference ◽  
Repeated Sampling

ECOLOGICAL DETERMINANTS OF “WHITE ETHNIC” IDENTITY IN ST. LOUIS, MISSOURI

1983 ◽  
Vol 11 (1) ◽  
pp. 49-57
Author(s):  
Irene Dabrowski
Keyword(s):  
Participant Observation ◽  
Research Participant ◽  
Ecological Framework ◽  
Interaction Patterns ◽  
Ethnic Communities ◽  
Organizational Activity ◽  
White Ethnic ◽  
The Relationship ◽  
Group Involvement ◽  
Center Site

A comparative analysis of voluntary group interaction patterns within two “white ethnic” groups in St. Louis was conducted to investigate the relationship between levels of voluntary group participation and geographical sites of respective ethnic centers. Archival research, participant observation, and structured interviewing over a 12-month period were the methods employed to conduct case studies of both the Croatian and Czech ethnic communities. Utilizing an ecological framework, the findings suggest a degree of organizational activity is strongly dependent on the environmental adequacy of the ethnic center site. This paper describes how two varying external locations promote contrasting styles of secondary group involvement. Neighborhood stability supports ongoing participation in one pattern, but in the other, area transiency exacts merely occasional participation.

scholarly journals Post-prediction inference

2020 ◽  
Author(s):  
Siruo Wang ◽  
Tyler H McCormick ◽  
Jeffrey T Leek
Keyword(s):  
Machine Learning ◽  
Statistical Inference ◽  
Variance Estimation ◽  
R Package ◽  
Outcome Data ◽  
Learning Framework ◽  
Autopsy Data ◽  
Validation Set ◽  
Low Dimensional ◽  
The Relationship

Many modern problems in medicine and public health leverage machine learning methods to predict outcomes based on observable covariates. In an increasingly wide array of settings, these predicted outcomes are used in subsequent statistical analysis, often without accounting for the distinction between observed and predicted outcomes. We call inference with predicted outcomes post-prediction inference. In this paper, we develop methods for correcting statistical inference using outcomes predicted with an arbitrary machine learning method. Rather than trying to derive the correction from the first principles for each machine learning tool, we make the observation that there is typically a low-dimensional and easily modeled representation of the relationship between the observed and predicted outcomes. We build an approach for the post-prediction inference that naturally fits into the standard machine learning framework, where the data is divided into training, testing, and validation sets. We train the prediction model in the training set,. We estimate the relationship between the observed and predicted outcomes on the testing set and use that model to correct inference on the validation set and subsequent statistical models. We show our postpi approach can correct bias and improve variance estimation (and thus subsequent statistical inference) with predicted outcome data. To show the broad range of applicability of our approach, we show postpi can improve inference in two totally distinct fields: modeling predicted phenotypes in re-purposed gene expression data and modeling predicted causes of death in verbal autopsy data. We have made our method available through an open-source R package: https://github.com/leekgroup/postpi

scholarly journals DYNAMICS OF DIGITAL MARKETS

2021 ◽  
Author(s):  
Anne Mette Thorhauge ◽  
Jingyan Elaine Yuan ◽  
Jacob Ørmen ◽  
Andreas Gregersen ◽  
Patrick Vonderau
Keyword(s):  
Economic Sociology ◽  
State Regulation ◽  
Open Market ◽  
Interaction Patterns ◽  
Economic Implications ◽  
Digital Platforms ◽  
Starting Point ◽  
Global Stock Markets ◽  
The Relationship ◽  
The Way

The focus of this panel is the material, organizational, and cultural conditions of digital markets. While the notion of economy refers to the more general production, distribution and allocation in society, the idea of markets represents specific contexts of economic exchange typical of capitalist economies (Carruthers & Babb, 2013). A more elaborate understanding of digital markets and their relationships with digital platforms can expand our understanding of the economic implications that specific types of platform architectures have at the level of economic interaction. The discussion takes as a starting point perspectives from economic sociology that emphasize how markets are embedded into broader social and societal structures (Granovetter, 2017) and conditioned upon cultural norms and conventions (Beckert, 2009). In addition, the panel is informed by the way economic sociology and STS have approached the material conditions of markets (Garcia-Parpet, 2007; MacKenzie, 2018) and the way these conditions frame and transform power relations and interaction patterns on specific markets. The panel consists of four papers that approach this issue from a range of perspectives: The relationship between platform architectures, open market strategies and the formation of ‘commodity money’ in the case of Steam, the relationship between platforms, markets, and state regulation in the case of Alibaba, the role of narratives, imagined futures, and collective action that frame patterns of buying and selling in global stock markets in the case of Gamestop shares and, finally, how the online engagement industry is organized in practice in the case of “click farms”.

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