scholarly journals Graphical Data Analysis

2021 ◽  
Vol 2020 (1) ◽  
pp. 1
Author(s):  
Paul Collett
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Quantitative Research ◽  
Statistical Significance ◽  
Academic Disciplines ◽  
Ongoing Debate ◽  
Statistical Significance Testing ◽  
Graphical Data ◽  
Quantitative Data Analysis

Limitations in statistical significance testing are an issue of ongoing debate in many academic disciplines. Moving away from a reliance on their use in quantitative research is seen as an important step towards improving the quality of such research. One area that can help here is graphical data analysis, both as an exploratory and explanatory tool. This paper presents an overview of graphical techniques for quantitative data analysis. After outlining the rationale for the use of graphical data analysis, consideration of the appropriate types of graphs to use is provided. A number of useful graphs, created using the R statistical package, are introduced, along with a link to the full code to reproduce the examples. Suggestions are presented for how graphical techniques can help with both the exploration and conformation stages in research. 統計的有意差検定の限界は、多くの学術分野で継続的に議論されている問題である。量的研究における統計的有意差検定への使用依存から脱却することは、研究の質を向上させるための重要なステップであると考えられる。ここで役立つのが、探索的・説明的なツールとしてのグラフデータ分析である。本稿は、定量的なデータ分析のためのグラフ技術の概要を説明する。グラフィカルなデータ分析を使用する理由を説明した後、使用するグラフの適切な種類について検討する。R統計パッケージを用いて作成された便利なグラフの数々を紹介し、例題を再現するための完全なコードへのリンクも掲載する。本稿は、研究における探索と適合の両方の段階で、グラフ技術がどのように役立つかを提案するものである。

scholarly journals PENDAMPINGAN MENINGKATKAN MUTU MANAJEMEN PAUD BINAAN

2021 ◽  
Vol 6 (1) ◽  
pp. 36-43
Author(s):  
Yecha Febrieanitha Putri ◽  
Indah Dwi Sartika ◽  
Fahmi Fahmi
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Action Plan ◽  
Participatory Action ◽  
Qualitative Data Analysis ◽  
Delivery Assistance ◽  
Quantitative Data Analysis ◽  
Using Data

The research aimed to find out whether the quality of PAUD management assistance could improve. Research-based service was carried out at RA Perwanida 3 and PAUD Kaisah. This study used the Participatory Action Research (PAR) model of the Kemmis, S. & McTaggart , R. Research methodology which was carried out in a series through online material delivery assistance and direct mentoring to each PAUD unit. The implementation of the activity is carried out in 5 steps, namely diagnosis, making an action plan, taking action, evaluating and reflecting. Data analysis using data analysis quantitative data analysis and qualitative data analysis. Quantitative data analysis was obtained from the description of the value of document completeness, pre and post mentoring. While the qualitative data analysis was obtained from field notes, documentation notes and interview notes using four parts, namely data reduction, display data and conclusion data. The results of the dedication research with assistance to improve the quality of the assisted PAUD management, the average document data obtained from each of the assisted institutions has increased by 37%, which is based on 30 assessment indicators, 26 indicators have been successfully fulfilled by each of the assisted PAUD institutions so that initially the average file completeness was 49% after being given assistance to 86%.

Quantitative Data Analysis

2021 ◽  
pp. 184-202
Keyword(s):  
Data Analysis ◽  
Statistical Analysis ◽  
Undergraduate Students ◽  
Quantitative Data ◽  
Quantitative Research ◽  
Research Projects ◽  
Quantitative Data Analysis ◽  
Non Parametric

This chapter discusses the analysis of data in quantitative research and the most common strategies to follow. Undergraduate students in most programmes may not necessarily need to use advanced statistical analysis. This chapter takes the readers through parametric and non-parametric tests. Readers will be able to grasp measurement tests that are appropriate for several quantitative data analysis in research projects. The differences between parametric and non-parametric tests are examined and explored in some detail. The assumptions for parametric and non-parametric measures are also highlighted and relevant examples provided and should enable the reader to select appropriate measures for their research projects.

Quantitative Data Analysis Approaches

2015 ◽  
Author(s):  
Babek Taheri ◽  
Catherine Porter ◽  
Christian Konig ◽  
Nikolaos Valantasis-Kanellos
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Quantitative Data ◽  
Quantitative Research ◽  
Descriptive Analysis ◽  
Statistical Techniques ◽  
Statistical Tools ◽  
Quantitative Data Analysis ◽  
Key Issues

In order to understand data and present findings in an accurate way, researchers and managers need to develop an awareness of statistical analysis techniques. This chapter focuses on two sets of the most widely used statistical tools – exploring relationships and comparing groups. It also briefly explains the nature of Big Data. This chapter explores the data preparation approach, how to conduct preliminary (descriptive) analysis as well as introducing some of the main statistical techniques used in quantitative research in business management. The key issues that should be related back to your study question are a) how to prepare your data; b) how to conduct preliminary data analysis; c) what analyses are appropriate for comparing groups; d) what techniques are most appropriate for exploring relationships.

scholarly journals The employment of online questionnaires within user studies research in school libraries.

2013 ◽  
Vol 30 (95) ◽  
pp. 25-32 ◽  
Author(s):  
Andrew K Shenton ◽  
Andrew Johnson
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Response Rate ◽  
School Libraries ◽  
Research Strategy ◽  
User Studies ◽  
Wide Range ◽  
Quantitative Data Analysis ◽  
E Mail

This paper considers the effectiveness of a research method based on online questionnaires and employed in a recent study of attitudes to books and school libraries among pupils in an English high school. The questionnaire was constructed in Microsoft SharePoint. ln an e-mail, the youngsters were asked to complete the questionnaire and were taken to it via a hyperlink. The research strategy ensured that, in theory at least, a wide range of pupils was reached. lt exploited their familiarity with electronic surveys and eliminated the problem of illegible handwriting often associated with paper questionnaires. Nevertheless, the response rate was poor and the quality of the data questionable despite several provisions for ensuring trustworthiness. The SharePoint system employed supported quantitative data analysis to a much greater extent than it did qualitative. The paper concludes by identifying other forms of electronic questionnaire that may be employed in schools that lack SharePoint software.

scholarly journals Damaging Real Lives through Obstinacy: Re-Emphasising Why Significance Testing is Wrong

2016 ◽  
Vol 21 (1) ◽  
pp. 102-115 ◽  
Author(s):  
Stephen Gorard
Keyword(s):  
Statistical Significance ◽  
Poor Quality ◽  
Significance Testing ◽  
Significance Tests ◽  
Statistical Significance Testing ◽  
Wrong Answer ◽  
Repeated Calls ◽  
Numeric Data ◽  
Quality Of Research

This paper reminds readers of the absurdity of statistical significance testing, despite its continued widespread use as a supposed method for analysing numeric data. There have been complaints about the poor quality of research employing significance tests for a hundred years, and repeated calls for researchers to stop using and reporting them. There have even been attempted bans. Many thousands of papers have now been written, in all areas of research, explaining why significance tests do not work. There are too many for all to be cited here. This paper summarises the logical problems as described in over 100 of these prior pieces. It then presents a series of demonstrations showing that significance tests do not work in practice. In fact, they are more likely to produce the wrong answer than a right one. The confused use of significance testing has practical and damaging consequences for people's lives. Ending the use of significance tests is a pressing ethical issue for research. Anyone knowing the problems, as described over one hundred years, who continues to teach, use or publish significance tests is acting unethically, and knowingly risking the damage that ensues.

scholarly journals The Other Half of the Story: Effect Size Analysis in Quantitative Research

2013 ◽  
Vol 12 (3) ◽  
pp. 345-351 ◽  
Author(s):  
Jessica Middlemis Maher ◽  
Jonathan C. Markey ◽  
Diane Ebert-May
Keyword(s):  
Educational Research ◽  
Effect Size ◽  
Quantitative Research ◽  
Statistical Significance ◽  
The Other ◽  
Practical Significance ◽  
Significance Testing ◽  
Size Analysis ◽  
Significance Tests ◽  
Statistical Significance Testing

Statistical significance testing is the cornerstone of quantitative research, but studies that fail to report measures of effect size are potentially missing a robust part of the analysis. We provide a rationale for why effect size measures should be included in quantitative discipline-based education research. Examples from both biological and educational research demonstrate the utility of effect size for evaluating practical significance. We also provide details about some effect size indices that are paired with common statistical significance tests used in educational research and offer general suggestions for interpreting effect size measures. Finally, we discuss some inherent limitations of effect size measures and provide further recommendations about reporting confidence intervals.

scholarly journals Meta Analisis Pengaruh Model Pembelajaran POE Terhadap Pemahaman Konsep

2019 ◽  
Vol 4 ◽  
pp. 174
Author(s):  
Dewanta Arya Nugraha ◽  
Arifian Dimas ◽  
C Cari ◽  
A Suparmi ◽  
Widha Sunarno
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Meta Analysis ◽  
Learning Model ◽  
Research Results ◽  
Purposive Sampling ◽  
Is Research ◽  
Research Theme ◽  
Quantitative Data Analysis

<p><strong>Abstract: </strong>This study aims to analyze the POE learning model for understanding physics concepts. The method used in this research is a meta-analysis. Meta-analysis is research that examines the results of similar studies. Data obtained from national and international journal documents taken by purposive sampling based on conformity with the research theme. Data analysis using quantitative data analysis with presentations and qualitative data analysis in the form of descriptions of research results found. Based on data analysis, it found that the POE learning model can improve students' understanding of concepts.</p><p> </p><p><strong>Abstrak: </strong>Penelitian ini bertujuan untuk menganalisis model pembelajaran POE terhadap pemahaman konsep fisika. Metode yang digunakan dalam penelitian ini adalah meta analisis. Meta analisis merupakan penelitian yang mengkaji hasil penelitian yang sejenis. Data diperoleh dari dokumen-dokumen jurnal nasional maupun internasional yang diambil secara purposive sampling berdasarkan kesesuaian dengan tema penelitian. Analisis data menggunakan analisis data kuantitatif dengan presentasen dan analisis data kualitatif berupa deskripsi-deskripsi hasil penelitian yang ditemui. Berdasarkan analisis data ditemukan bahwa model pembelajaran POE dapat meningkatkan pemahaman konsep siswa</p>

scholarly journals Peningkatan Kemampuan Penyusunan Rencana Pelaksanaan Pembelajaran Guru MIN Amkoteng melalui Supervisi Akademik

Al Adzka ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 77
Author(s):  
Berkati Berkati
Keyword(s):  
Data Analysis ◽  
Action Research ◽  
Primary Schools ◽  
Quantitative Data ◽  
National Education ◽  
Quantitative Data Analysis ◽  
Planning Implementation ◽  
Implementation Plans

The purpose of this study was to determine the increase in the ability of teachers in preparing Learning Implementation Plans (RPP) through academic supervision. This research is a school action research with steps: planning, implementation, observation, and reflection. This research is planned to consist of two cycles. This research was carried out at MIN Amkoteng Subdistrict Anjir Muara, Barito Kuala District, South Kalimantan Province. Quantitative data analysis was used to determine the increase in the value of the practice of making RPP by teachers based on the standards set by the Ministry of National Education. The results of the study show that the teacher's ability to prepare RPP can be improved by academic supervision; collaboration between teachers and Supervisors of Primary Schools can be well established and useful in fostering teachers to improve their abilities in preparing RPP; the complete document II of the Education Unit (KTSP) MIN Amkoteng curriculum is complete, in the form of RPP collection documents; and this academic supervision can be used as a model in the following years in terms of drafting RPP, and can be used as an example for other schools.

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