Discrimination and interpretation of errors in statistical analysis of quantitative data in medical papers

2007 ◽  
pp. 481-484 ◽  
Author(s):  
Liangping Hu
Keyword(s):  
Statistical Analysis ◽  
Quantitative Data

Delphi Method in a Digital Age

2018 ◽  
pp. 132-151
Author(s):  
Christine A. Haynes ◽  
Kaye Shelton
Keyword(s):  
Statistical Analysis ◽  
Delphi Method ◽  
Quantitative Data ◽  
Online Survey ◽  
Research Collaboration ◽  
Communication Strategies ◽  
Digital Age ◽  
Research Approach ◽  
Qualitative And Quantitative ◽  
Delphi Studies

With the rapid advancement of online survey tools, research collaboration tools, communication platforms, and statistical analysis tools, the Delphi method is an increasingly popular research approach to gain insight from experts into complex problems or when future-oriented planning is required. This chapter focuses on practical considerations and implications for practice when conducting studies online using the Delphi method. Practical logistics for the management of online Delphi studies explored in this chapter include preparing for a successful study, designing communication strategies, addressing technological considerations, and handling of qualitative and quantitative data.

Research in Cyprus

2020 ◽  
pp. 134-142
Keyword(s):  
Statistical Analysis ◽  
Media Coverage ◽  
Quantitative Data ◽  
Educational Background ◽  
Online Media ◽  
Statistical Graphics ◽  
Variable Analysis

This chapter presents data gathered by a Cyprus-related survey that was conducted by the authors with the aid of many professional Cypriot journalists. The survey was conducted between 6th of September and 13th of November 2012 and managed to gather 62 responses. The participants came from a different social and educational background as they were gathered thanks to online media coverage. The authors present statistical graphics in order to visualise the quantitative data. Additionally, statistical analysis is being conducted (using one by one variable analysis) in order to identify trends and associations between different groups in the same country.

Research in Germany

2020 ◽  
pp. 100-108
Keyword(s):  
Statistical Analysis ◽  
Quantitative Data ◽  
Teaching Staff ◽  
Research Assistant ◽  
Statistical Graphics ◽  
Highly Educated ◽  
Variable Analysis

This chapter presents data gathered by a Germany-related survey that was conducted by the authors between 29th of November and 18th of December 2011, with the aid of Johannes Fritz (Research Assistant at Friedrich-Alexander Universität Erlangen-Nürnberg). The sample was limited but highly educated, consisting mainly of students and teaching staff of the Friedrich-Alexander Universität Erlangen-Nürnberg. The authors present statistical graphics in order to visualise the quantitative data. Additionally, statistical analysis is being conducted (using one by one variable analysis) in order to identify trends and associations between different groups in the same country.

Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite

2022 ◽  
pp. 417-451
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Statistical Analysis ◽  
Survey Research ◽  
Quantitative Data ◽  
Q Methodology ◽  
Online Survey ◽  
Analysis Tool ◽  
Q Method ◽  
Statistical Analysis Tool ◽  
Q Sort ◽  
Basic Statistical Analysis

The q-method, as a graphic (visual) elicitation, has existed since the mid-1930s. Setting up a q-method, with q-sort capabilities, in an online survey platform, extends the reach of this method, even as data has to be processed in a quantitative data analytics suite. This chapter describes the setting up of a visual q-sort and the related debriefing on the Qualtrics Research Suite. The available data may be extracted and analyzed in a basic statistical analysis tool for factors and preference clusters.

Secondary Analysis for Digitized Data

2022 ◽  
pp. 898-919
Author(s):  
Gennaro Iorio ◽  
Marco Palmieri ◽  
Geraldina Roberti
Keyword(s):  
Statistical Analysis ◽  
Empirical Study ◽  
Quantitative Data ◽  
Research Method ◽  
Social Research ◽  
Secondary Analysis ◽  
Well Being ◽  
Digital Society ◽  
National Perspective ◽  
The Web

Secondary analysis for quantitative data is a social research method traditionally employed for statistical analysis of administrative data. In the new digital society, this old research method that pre-existed the emergence of the new digital environment has been digitized to carry out its valuable activity in doing science. In this chapter, the secondary analysis for digitized data is illustrated. Thanks to the growing availability of datasets digitized on the web, the scholars of social well-being use the secondary analysis to inquiry this phenomenon through a cross-national perspective. The authors present the empirical study of World Love Index, in which the utility of the secondary analysis in finding and selecting valid indicators of social well-being is experienced.

scholarly journals A stepwise method for annotating appraisal

2018 ◽  
Vol 25 (2) ◽  
pp. 229-258 ◽  
Author(s):  
Matteo Fuoli
Keyword(s):  
Statistical Analysis ◽  
Best Practices ◽  
Quantitative Data ◽  
Manual Annotation ◽  
Methodological Issues ◽  
Stepwise Method ◽  
Evaluative Language ◽  
Practical Tool ◽  
The Creation ◽  
Context Specific

Abstract Despite a growing awareness of methodological issues, the literature on appraisal has not so far provided adequate answers to some of the key challenges involved in reliably identifying and classifying evaluative language expressions. This article presents a stepwise method for the manual annotation of appraisal in text that is designed to optimize reliability, replicability and transparency. The procedure consists of seven steps, from the creation of a context-specific annotation manual to the statistical analysis of the quantitative data derived from the manually-performed annotations. By presenting this method, the article pursues the twofold purpose of (i) providing a practical tool that can facilitate more reliable, replicable and transparent analyses, and (ii) fostering a discussion of the best practices that should be observed when manually annotating appraisal.

scholarly journals Characteristics of Team Leaders Play as exemplified by the European Championships In Basketball

2011 ◽  
Vol 27 (1) ◽  
pp. 161-179
Author(s):  
Beata Pluta ◽  
Marcin Andrzejewski
Keyword(s):  
Comparative Analysis ◽  
Statistical Analysis ◽  
Statistical Methods ◽  
Empirical Data ◽  
Quantitative Data ◽  
Team Sports ◽  
Team Leaders ◽  
Qualitative And Quantitative ◽  
Basketball Team

Characteristics of Team Leaders Play as exemplified by the European Championships In BasketballThis paper presents a statistical analysis of basketball team leaders performance during a championship status tournament in team sports using the example of the 36th European Championships EuroBasket 2009. The list of player-leaders of particular national teams was developed by means of the expert method, based on the analysis of qualitative and quantitative data. Empirical data gathered were taken from the website of EuroBasket 2009 Poland (www.eurobasket2009.org) and FIBA Europe (www.fiba.com). Formal statistical methods concerning sample description were used. The comparative analysis was conducted by means of various tabular and graphic techniques. The calculations were performed in a STATISTICA spreadsheet. The applied statistical methods allowed a series of conclusions to be drawn concerning the performance of leader-players and their cooperation with other players on the court. The knowledge of particular SGCs (standard game components) realization allows those dispositions of leader-players which are especially significant in the process of cooperation in a basketball team to be improved by coaching.

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