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Management of Utilizing Data Analysis and Hypothesis Testing in Improving the Quality of Research Reports

APTISI Transactions on Management (ATM) · Vol. 2 No. 2 (2019) · pp. 159–167

DOI
10.33050/atm.v2i2.789
ISSN
2622-6804, 2622-6812
Published
2019-01-25
Publisher
Pandawan
Language
en
License
creativecommons.org/licenses/by-sa/4.0

Abstract

English

Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses.

Indonesian

Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses. Keywords: Data analysis, Quantitative research, Qualitative research, Hypothesis

Keywords

Collaboration network of the authors

40 authors · 120 co-authorship links · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Raharja
  • Universitas Amikom Purwokerto
  • Universitas Catur Insan Cendekia Cirebon
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Tuti NurhaeniAffiliation unknown2
Alfri AdiwijayaAffiliation unknown2
Ihsan Nuril HikamAffiliation unknown2
Dwi JulianingsihAffiliation unknown2
Ageng Setiani RafikaAffiliation unknown2
Qurotul AiniUniversitas Raharja2
Untung RahardjaAffiliation unknown2
Ninda LutfianiUniversitas Raharja1
Ankur SinghAffiliation unknown1
Widya FebrianiAffiliation unknown1
Nuke Puji Lestari SantosoAffiliation unknown1
Amitkumar DudhatAffiliation unknown1
Husni Teja SukmanaAffiliation unknown1
Aditya MardiansyahAffiliation unknown1
Dewi ImmaniarAffiliation unknown1
Dedeh SupriyantiAffiliation unknown1
Nanda SeptianiAffiliation unknown1
Nur AzizahAffiliation unknown1
Hilda HildaAffiliation unknown1
Aan KaniviaAffiliation unknown1
Muhammad Faizal FazriAffiliation unknown1
Sabda MaulanaAffiliation unknown1
Hetilaniar HetilaniarAffiliation unknown1
Semaria Eva Elita GirsangAffiliation unknown1
Souza Nurafrianto Windiartono PutraAffiliation unknown1
Kawl W KartsAffiliation unknown1
Taqwa HarigunaUniversitas Amikom Purwokerto1
Agung PriyadiAffiliation unknown1
Ankur Singh BistAffiliation unknown1
Megha UpretiAffiliation unknown1
Chitra PandeyAffiliation unknown1
Buphest RawatAffiliation unknown1
Hiroshi KentaAffiliation unknown1
Mochamad Heru Riza ChakimAffiliation unknown1
Lena MagdalenaAffiliation unknown1
Chandra LukitaUniversitas Catur Insan Cendekia Cirebon1
Goh YaoAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ijc.ilearning.co/ATM/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Management of Utilizing Data Analysis and Hypothesis Testing in Improving the Quality of Research Reports</dc:title>
	<dc:title xml:lang="id">Management of Utilizing Data Analysis and Hypothesis Testing in Improving the Quality of Research Reports</dc:title>
	<dc:creator xml:lang="en">Yusup, Muhamad</dc:creator>
	<dc:creator xml:lang="en">Syauqi Naufal, Romzi</dc:creator>
	<dc:creator xml:lang="en">Hardini, Marviola</dc:creator>
	<dc:subject xml:lang="en">Data analysis</dc:subject>
	<dc:subject xml:lang="en">Quantitative research</dc:subject>
	<dc:subject xml:lang="en">Qualitative research</dc:subject>
	<dc:subject xml:lang="en">Hypothesis</dc:subject>
	<dc:description xml:lang="en">Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses.</dc:description>
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Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses.
Keywords: Data analysis, Quantitative research, Qualitative research, Hypothesis



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	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2019-01-25</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://ijc.ilearning.co/ATM/article/view/789</dc:identifier>
	<dc:identifier>10.33050/atm.v2i2.789</dc:identifier>
	<dc:source xml:lang="en">APTISI Transactions on Management (ATM); Vol. 2 No. 2 (2018): July; 159-167</dc:source>
	<dc:source xml:lang="id">APTISI Transactions on Management (ATM); Vol 2 No 2 (2018): ATM (APTISI Transactions on Management); 159-167</dc:source>
	<dc:source>2622-6804</dc:source>
	<dc:source>2622-6812</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://ijc.ilearning.co/ATM/article/view/789/180</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2018 Muhamad Yusup, Romzi Syauqi Naufal, Marviola Hardini (Author)</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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