scholarly journals Common mistakes in data presentation and statistical analysis: how can the BioStat Decision Tool help?

2013 ◽  
Author(s):  
Siouxsie Wiles ◽  
Anne L Bishop
Keyword(s):  
Scientific Literature ◽  
Statistical Tests ◽  
Statistical Test ◽  
Statistical Techniques ◽  
Sample Collection ◽  
Decision Tool ◽  
Data Presentation ◽  
Journal Editors ◽  
Molecular Microbiology ◽  
User Friendly

As medical and molecular microbiologists who regularly read the scientific literature, it is our impression that many published papers contain data that is inappropriately presented and/or analysed. This is borne out by a number of studies which indicate that typically at least half of published scientific articles that use statistical methods contain statistical errors. While there are an abundance of resources dedicated to explaining statistics to biologists, the evidence would suggest that they are largely ineffective. These resources tend to focus on how particular statistical tests work, with reams of complicated-looking mathematical formulae. In addition, many statisticians are unfamiliar with the application of statistical techniques to molecular microbiology, instead telling us we need more samples, which can be difficult both ethically and practically in fields that include animal work and painstaking sample collection. In an age where performing a statistical test merely requires clicking a button in a computer programme, it could be argued that what the vast majority of biologists need is not mathematical formulae but simple guidance on which buttons to click. We have developed an easy to follow decision chart that guides biologists through the statistical maze. Our practical and user friendly chart should prove useful not only to active researchers, but also to journal editors and reviewers to rapidly determine if data presented in a submitted manuscript has been correctly analysed.

scholarly journals Common mistakes in data presentation and statistical analysis: how can the BioStat Decision Tool help?

2013 ◽  
Author(s):  
Siouxsie Wiles ◽  
Anne L Bishop
Keyword(s):  
Scientific Literature ◽  
Statistical Tests ◽  
Statistical Test ◽  
Statistical Techniques ◽  
Sample Collection ◽  
Decision Tool ◽  
Data Presentation ◽  
Journal Editors ◽  
Molecular Microbiology ◽  
User Friendly

As medical and molecular microbiologists who regularly read the scientific literature, it is our impression that many published papers contain data that is inappropriately presented and/or analysed. This is borne out by a number of studies which indicate that typically at least half of published scientific articles that use statistical methods contain statistical errors. While there are an abundance of resources dedicated to explaining statistics to biologists, the evidence would suggest that they are largely ineffective. These resources tend to focus on how particular statistical tests work, with reams of complicated-looking mathematical formulae. In addition, many statisticians are unfamiliar with the application of statistical techniques to molecular microbiology, instead telling us we need more samples, which can be difficult both ethically and practically in fields that include animal work and painstaking sample collection. In an age where performing a statistical test merely requires clicking a button in a computer programme, it could be argued that what the vast majority of biologists need is not mathematical formulae but simple guidance on which buttons to click. We have developed an easy to follow decision chart that guides biologists through the statistical maze. Our practical and user friendly chart should prove useful not only to active researchers, but also to journal editors and reviewers to rapidly determine if data presented in a submitted manuscript has been correctly analysed.

Working with psychology journal editors to correct problems in the scientific literature.

2020 ◽  
Vol 61 (4) ◽  
pp. 342-348
Author(s):  
Harris L. Friedman ◽  
Douglas A. MacDonald ◽  
James C. Coyne
Keyword(s):  
Scientific Literature ◽  
Journal Editors

scholarly journals Is preregistration worthwhile?

2019 ◽  
Author(s):  
Aba Szollosi ◽  
David Kellen ◽  
Danielle Navarro ◽  
Rich Shiffrin ◽  
Iris van Rooij ◽  
...  
Keyword(s):  
Statistical Models ◽  
Statistical Tests ◽  
Error Rates ◽  
Statistical Techniques ◽  
Weak Version ◽  
Strong Version ◽  
Statistical Problems

Proponents of preregistration argue that, among other benefits, it improves the diagnosticity of statistical tests [1]. In the strong version of this argument, preregistration does this by solving statistical problems, such as family-wise error rates. In the weak version, it nudges people to think more deeply about their theories, methods, and analyses. We argue against both: the diagnosticity of statistical tests depend entirely on how well statistical models map onto underlying theories, and so improving statistical techniques does little to improve theories when the mapping is weak. There is also little reason to expect that preregistration will spontaneously help researchers to develop better theories (and, hence, better methods and analyses).

scholarly journals Guidelines for performing Mendelian randomization investigations

2020 ◽  
Vol 4 ◽  
pp. 186 ◽  
Author(s):  
Stephen Burgess ◽  
George Davey Smith ◽  
Neil M. Davies ◽  
Frank Dudbridge ◽  
Dipender Gill ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Data Sources ◽  
Sensitivity Analyses ◽  
Primary Analysis ◽  
Data Presentation ◽  
Journal Editors ◽  
Robust Statistical Methods

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 18 months.

scholarly journals ANALISIS TINGKAT KESESUAIAN DARI KLASIFIKASI KEPADATAN LALU LINTAS DAN WAKTU TEMPUH GOOGLE MAPS

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Laksita Amelia Paramesti ◽  
Dedi Atunggal
Keyword(s):  
Travel Time ◽  
Statistical Tests ◽  
Statistical Test ◽  
Traffic Information ◽  
Actual Condition ◽  
Traffic Density ◽  
Traffic Classification ◽  
Google Maps ◽  
Traffic Condition ◽  
Significant Difference

 Traffic congestion is one of problem that occur in big cities, therefore people need traffic information to determine traffic condition. One of many applications that provides traffic information is Google Maps. From the information generated, there are insuitability between google maps’s traffic update and travel time with the actual condition. So the aim of this study is to analyze the suitability level of traffic density classification and google maps travel time. Based on the speed range by Google, the level of suitability can be determined, while the google maps travel time is done by statistical tests. The statistical test used is a statistical test of two parameters using table t with 95% confidence level. The results of this study indicate that the level of suitability of the traffic classification only reaches 35%. The low level of suitability is caused by network latency. While information on google maps travel time does not have a significant difference in actual time.

Dynamical Analysis of Time Series by Statistical Tests

1997 ◽  
Vol 07 (12) ◽  
pp. 2629-2652 ◽  
Author(s):  
Gustavo Deco ◽  
Christian Schittenkopf ◽  
Bernd Schürmann
Keyword(s):  
Time Series ◽  
Information Flow ◽  
Statistical Tests ◽  
Statistical Test ◽  
Dynamical Analysis ◽  
Fourier Space ◽  
Statistical Framework ◽  
Temporal Structures ◽  
Analysis Of Time Series

In this review we deal with the application of statistical test techniques for the extraction of structures in time series. Two kinds of questions are answered in this statistical framework: Are there any temporal dependences in the data? and Which kind of dynamics generate these temporal dependences? The first question is known as the problem of predictability and also considers the aspect of stationarity. The second question is deeper in the sense that it deals with the dynamical characterization of the detected temporal structures. Central to our approach is a cumulant-based measure of statistical dependences in Fourier space. The dynamical aspects are studied by means of the information flow. The theory is illustrated by artificial and real-world, stochastic and chaotic examples.

scholarly journals PENGARUH NON PERFORMING FINANCING DAN PERSENTASE BAGI HASIL TERHADAP PEMBIAYAAN MUSYARAKAH PADA PT BANK SYARIAH MANDIRI

2019 ◽  
Vol 1 (1) ◽  
pp. 77-88
Author(s):  
Nora Ulfa ◽  
Ismaulina Ismaulina ◽  
Fathul Liza
Keyword(s):  
Significant Influence ◽  
Statistical Tests ◽  
Research Question ◽  
Profit Sharing ◽  
Positive Influence ◽  
Statistical Test ◽  
Financial Statement ◽  
Islamic Banking ◽  
Test Results ◽  
Production Sharing

Non Performing Financing (NPF) and Percentage of Profit Sharing (PBH) indirectly influence the distribution of Musyarakah financing to Islamic banking. NPF occurs because the customer is unable to pay installments from the musyarakah financing that he has received, the inability of the customer to pay monthly installments is due to the percentage of profit sharing that is too high. The phenomenon that has been happening to PT Bank Syariah Mandiri, namely the distribution of funding did not increase significantly due to an increase in NPF. Based on these thoughts, in this study a research question was taken to find out what factors would influence the distribution of funding to PT Bank Syariah Mandiri. Based on this phenomenon, the distribution of Musyarakah Financing to PT Bank Syariah Mandiri can be seen from the percentage of revenue sharing that has increased significantly, while the NPF and Financing have an interrelated relationship. It can be seen from the Financing data from 2012 to 2014 that the increase in financing was very small due to the increasing value of the NPF. The research method used is a quantitative method in which financial statement data taken through the official website www.syariah.mandiri.co.id will be processed through SPSS data. The results of the study are: The development of NPF of Syariah Mandiri Bank during 2012-2014 has fluctuated, where the percentage of NPF sometimes goes up and sometimes goes down, the results of statistical tests show Non Performing Financing (NPF) has a positive and significant influence on the distribution of Musyarakah Financing to Bank Syariah Mandiri. Because the significance value is smaller than 0.05. This indicates an increase and decrease in the amount of Musyarakah financing disbursed is strongly influenced by the NPF. The development of Bank Syariah Mandiri's Production Sharing Percentage (PBH) during 2012-2014 sometimes increased and sometimes decreased, the statistical test results showed that the Production Sharing Percentage (PBH) had a positive influence and had a significant influence on the distribution of Musyarakah Financing to Bank Syariah Mandiri. Because the significance value is smaller than 0.05. Keyword : Non Performing Financing,  Share of Percentage, Musyarakah Financing.   Abstrak Non Performing Financing (NPF) dan Persentase Bagi Hasil (PBH) secara tidak langsung mempengaruhi distribusi pembiayaan Musyarakah ke perbankan syariah. NPF terjadi karena pelanggan tidak mampu membayar cicilan dari pembiayaan musyarakah yang telah ia terima, ketidakmampuan pelanggan untuk membayar cicilan bulanan disebabkan oleh persentase pembagian keuntungan yang terlalu tinggi. Fenomena yang telah terjadi pada PT Bank Syariah Mandiri, yaitu penyaluran dana tidak meningkat secara signifikan karena adanya peningkatan NPF. Berdasarkan pemikiran ini, dalam penelitian ini pertanyaan penelitian diambil untuk mengetahui faktor-faktor apa yang akan mempengaruhi distribusi dana ke PT Bank Syariah Mandiri. Berdasarkan fenomena ini, distribusi Pembiayaan Musyarakah ke PT Bank Syariah Mandiri dapat dilihat dari persentase bagi hasil yang meningkat secara signifikan, sedangkan NPF dan Pembiayaan memiliki hubungan yang saling terkait. Dapat dilihat dari data Pembiayaan 2012-2014 bahwa peningkatan pembiayaan sangat kecil karena meningkatnya nilai NPF. Metode penelitian yang digunakan adalah metode kuantitatif dimana data laporan keuangan yang diambil melalui situs resmi www.syariah.mandiri.co.id akan diproses melalui data SPSS. Hasil dari penelitian ini adalah: Perkembangan NPF Bank Syariah Mandiri selama 2012-2014 mengalami fluktuasi, dimana persentase NPF terkadang naik dan terkadang turun, hasil uji statistik menunjukkan Non Performing Financing (NPF) memiliki hasil positif. dan pengaruh yang signifikan terhadap distribusi Pembiayaan Musyarakah ke Bank Syariah Mandiri. Karena nilai signifikansi lebih kecil dari 0,05. Ini menunjukkan peningkatan dan penurunan jumlah pembiayaan Musyarakah yang disalurkan sangat dipengaruhi oleh NPF. Perkembangan Persentase Bagi Hasil (PBH) Bank Syariah Mandiri selama 2012-2014 terkadang meningkat dan terkadang menurun, hasil uji statistik menunjukkan bahwa Persentase Bagi Hasil (PBH) berpengaruh positif dan berpengaruh signifikan terhadap penyaluran Pembiayaan Musyarakah. ke Bank Syariah Mandiri. Karena nilai signifikansi lebih kecil dari 0,05. Kata kunci: Non Performing Financing, Persentase Bagi Hasil, Pembiayaan Musharakah.

scholarly journals Studi Pemisahan Aliran Dasar Metode Local Minimum Method Daerah Aliran Sungai Miu

2021 ◽  
pp. 143-148
Author(s):  
S.R. Oktavia ◽  
O.A. Mantika ◽  
Rugaiyah Rugaiyah
Keyword(s):  
Local Minimum ◽  
River Flow ◽  
Statistical Tests ◽  
Flood Management ◽  
Statistical Test ◽  
Base Flow ◽  
Discharge Data ◽  
Permeability Characteristics ◽  
Measurement Results ◽  
Office Software

The two main elements of a river flow hydrograph are direct runoff and baseflow. Base flow is a flow that comes from groundwater and it is available during the rainy and dry seasons. Information of baseflow value of a watershed has an important meaning in efforts to develop and manage water resources, including the provision of clean water, irrigation systems, flood management and others. Miu watershed located in Sigi Regency often experiences natural disasters such as floods and droughts that occur almost every year, which is the research location with an area of 65,452.01 Ha. This study aims to determine the value of baseflow using the Local Minimum Method and to find out whether this method can be used for baseflow modeling in research watersheds. This study was conducted using Hydro Office software with input data in the form of daily discharge data from 2004 to 2013. The average baseflow value obtained was 5.43 m3/s. The process of calibrating the baseflow value by taking flow data in the dry season where there is no rainfall input. It is obtained that BFI have value an average of 0.89. This value indicates that the Miu watershed has high storage permeability characteristics, The Miu watershed has quite stable flow during dry periods, because the greater the BFI value, the better the water supply in a watershed. In the statistical test, the observed discharge is the discharge data from the measurement results for the period 2004-2013, while the calculated discharge is the result of the estimated base flow value obtained using the graphical method. From the results of the statistical test of RMSE and R2, the RMSE value was 0.147 and the R2 value was 0.751. Both statistical tests show that the local minimum method has a fairly good performance in modeling the base flow in the Miu watershed.

scholarly journals How feasible is it to abandon statistical significance? A reflection based on a short survey

2019 ◽  
Author(s):  
Fredi Alexander Diaz-Quijano ◽  
Fernando Morelli Calixto ◽  
José Mário Nunes da Silva
Keyword(s):  
Scientific Literature ◽  
Statistical Tests ◽  
Scientific Evidence ◽  
Statistical Significance ◽  
Wide Distribution ◽  
P Value ◽  
Scientific Publications ◽  
Inappropriate Use ◽  
Significant Term ◽  
Harsh Criticism

Abstract Background : There is a growing trend in using the “statistically significant” term in the scientific literature. However, harsh criticism of this concept motivated the recommendation to withdraw its use of scientific publications. We aimed to validate the support and the feasibility of adherence to this recommendation, among researchers having declared in favor of removing the statistical significance. Methods : We surveyed signatories of an article published that defended this recommendation, to validate their opinion and ask them about how likely they will retire the concept of statistical significance. Results: We obtained 151 responses which confirmed the support for the mentioned publication in aspects such as the adequate interpretation of the p-value, the degree of agreement, and the motivations to sign it. However, there was a wide distribution of answers about how likely are they to use the concept of "statistical significance” in future publications. About 42% declared being neutral, or that would likely use it again. We described arguments referred by several signatories and discussed aspects to be considered in the interpretation of research results. Conclusions : The declared position against the use of statistical significance had had legitimate support from numerous researchers. However, the full application of this recommendation does not seem feasible. The arguments related to the inappropriate use of statistical tests should promote more education among researchers and users of scientific evidence.

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