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Sample Size Comparison with r-programming between Two ANOM: Type Methods for Testing the Homogeneity of Variances

JOUrNAL OF THE INDIAN SOCIETY FOr PrOBABILITY AND STATISTICS 2020年第1期21卷 135-154页

作者： Pran Kumar, M. Anjaneyulu, G. V. S. r. Acharya Nagarjuna Univ Dept Stat Guntur 522510 Andhra Pradesh India

Pran Kumar and Anjaneyulu (Int J Phys Appl Sci 3:34-40, 2016) and Pran Kumar and Anjaneyulu (Bull Math Stat res 5:54-58, 2017) derived two sample size expressions for two ANOM-type methods developed by rao and Harikrishna (J Appl Stat 24:279-287, 1997) and Pran Kumar and rao (Commun Stat Simul Comput 27:459-468, 1998) respectively for testing the homogeneity of several variances. In this article, an empirical comparative study is done with r-software code programming of r Core Team (r: a language and environment for statistical computing, r Foundation for Statistical Computing, Vienna, 2019) for the sample sizes derived by Pran Kumar and Anjaneyulu (2016, 2017) between the two methods developed by rao and Harikrishna (1997) and Pran Kumar and rao (1998). The study is carried to detect the significance of one of the population variance among k normal population variances from their grand average by at least a specified amount 'd' for fixed level of significance alpha and fixed power P in the case of equal sample sizes. The specified amount Delta in the sample size given by Pran Kumar and Anjaneyulu (2016) and the specified amount D in the sample size given by Pran Kumar and Anjaneyulu (2017) are derived in terms of some common amount 'd' for comparison. The tables of comparison of sample sizes are given particularly for one of the significant variance taken as unity among k variances from their grand average and for alpha =0.01, 0.05, P=0.8, 0.9, 0.95, 0.99, d=1, 3, 5, k=3(1) 20, 30, 60, The comparison reveals that the sample size derived by Pran Kumar and Anjaneyulu (2017) for the method developed by Pran Kumar and rao (1998) is less than that of the sample size derived by Pran Kumar and Anjaneyulu (2016) for the method developed rao and Harikrishna (1997).

关键词： Analysis of means Comparison between sample sizes Normality Power r-programming Variances

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Potential use of r-statistical programming in the field of geoscience 2

Potential use of R-statistical programming in the field of g...

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2nd International Conference for Convergence in Technology (I2CT)

作者： Bishwal, r. M. IIT Indian Sch Mines ISM Dept Min Engn Dhanbad Bihar India

ISBN: (纸本)9781509043071

Computational and statistical assessment of data has become the most valuable resource in every field including geoscience for making accurate decision. Analysis of soil and earth structures requires complex mathematical and numerical simulation which demands significant expertise and resources inciting costlier and tedious tasks. The unavailability of proper open-source tools and technical resources has resulted in limited flow of know ledge among the research communities. These resources, however, when available is not easy to understand due to its complexity in data analysis and results interpretation, and restricted mostly to the original contributor. This paper presents some recent developments in geoscience field such as geology, remote sensing, soil and rock mechanics where the open-source tool r-programming can be used in statistical research and understandings. It also describes the list of packages available in r-programming for specific field of study and how it can be used to promote open and reproducible research.

关键词： Geoscience Open-source r-programming reproducible research

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Teaching Academic Staff to Implement Interactive Graphics for Their Courses

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TECHNOLOGY KNOWLEDGE AND LEArNING 2024年第1期29卷 113-134页

作者： Liebig, Pamela Filor, Viviane Scheumann, Mariana Buchholz, Martina Jung, Klaus Univ Vet Med Hannover Inst Anim Breeding & Genet Bunteweg 17p D-30559 Hannover Germany Univ Vet Med Hannover Dept Pharmacol Toxicol & Pharm Hannover Germany Univ Vet Med Hannover Inst Zool Hannover Germany Univ Vet Med Hannover Inst Food Toxicol Hannover Germany

Many academic teachers present data as static graphics in their lectures and courses. However, data structures have become more complex in the last decades, especially in the biomedical disciplines, and interactive graphics can provide a better means to communicate the scientific contents to students. Besides, the technological qualifications of academic staff are diverse, and it has been little studied how these teachers can be trained to program and implement interactive graphics for their courses. It is also little known whether interactive graphics will be helpful for teaching and learning. We conducted a pilot online workshop to identify aspects that need to be addressed when teaching academic staff to program interactive graphics in form of Shiny-apps based on the programing language r. The n = 25 participants were academic staff from the fields of medicine or natural sciences. Pre- and post-workshop questionnaires were used to identify which aspects should be considered in future workshops, to query the usefulness of interactive graphics for teachers and students, and to identify the impact of the workshop on the teacher's opinion towards digital teaching devices and their preparedness to program own interactive graphics. Most participants showed strong interest to use interactive graphics in their courses after the workshop, and interactive graphics were overall rated as very helpful for teachers and students. However, only those with prior programming knowledge intended to implement own graphics. We conclude that an extension of the workshop will be necessary to provide additional training for participants with no background in r programming.

关键词： Interactive graphics Professional development r-programming r-shiny Workshop

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Live Bird Webcams Engage College Introductory Biostatistics Students

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AMErICAN BIOLOGY TEACHEr 2023年第4期85卷 203-206页

作者： Olson, Gardner W. Moody, Eric K. Middlebury Coll Dept Biol Middlebury VT 05753 USA

Data manipulation and statistical analysis are increasingly important learning goals for undergraduate biology majors, yet many biology students approach statistics courses with apprehension. We designed a set of activities to use engaging subject matter, bird feeder webcams located throughout the Western Hemisphere, to foster a growth mindset by gradually building on data analysis and experimental design skills, using the American Statistical Association's educational guidelines.

关键词： inquiry statistical analysis ornithology university r-programming GAISE

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Coupled application of r and WetSpa models for assessment of climate change impact on streamflow of Werie Catchment, Tigray, Ethiopia

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JOUrNAL OF WATEr AND CLIMATE CHANGE 2021年第3期12卷 916-936页

作者： Kidanemariam, Selam Goitom, Haddush Desta, Yigzaw Mekelle Univ Sch Civil Engn Ethiopian Inst Technol Mekelle Mekelle Ethiopia

This research assesses the streamflow response of Werie river to climate change. Baseline (1980-2009) climate data of precipitation, maximum and minimum temperature were analyzed using delta based statistical downscaling approach in r software packages to predict future 90-year (2010-2099) periods under two emission scenarios of representative Concentration Pathways (rCP) 4.5 and rCP 8.5, indicating medium and extremely high emission scenarios respectively. Generated future climate variables indicate Werie will experience a significant increase in precipitation, and maximum and minimum air temperature for both rCPs. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) was applied to assess the water balance of Werie river. The WetSpa model reproduced the streamflow well with performance statistics values of r-2 = 0.84 and 0.85, Nash-Sutcliffe efficiency = 0.72 and 0.72, and model bias = -0.14 and -0.15 for the calibration data set of 1999-2010 and validation data of 2011-2014, respectively. Finally, by taking the downscaled future climate variables as input, WetSpa future prediction shows that there will be an increase in the Werie catchment mean annual streamflow up to 29.6% for rCP 4.5 and 35.6% for rCP 8.5 compared to the baseline period.

关键词： climate change Ethiopia rCP r-programming streamflow WetSpa

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The r-package surveysd: Estimating standard errors for complex surveys with a rotating panel design

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Statistical Journal of the IAOS 2021年第1期37卷 115-121页

作者： Gussenbauer, Johannes De Cillia, Gregor Statistics Austria Guglgasse 13 Vienna 1110 Austria

Surveys with a rotating panel design are a prominent tool for producing more efficient estimates for indicators regarding trends or net changes over time. Variance estimation for net changes becomes however more complicated due to a possibly high correlation between the panel waves. Therefore, these estimates are quite burdensome to produce with traditional means. With the r-package surveysd, we present a tool which supports a straightforward way for producing estimates and corresponding standard errors for complex surveys with a rotating panel design. The package uses bootstrap techniques which incorporate the panel design and thus makes it easy to estimate standard errors. In addition the package supports a method for producing more efficient estimates by cumulating multiple consecutive sample waves. This method can lead to a significant decrease in variance assuming that structural patterns for the indicator in question remain fairly robust over time. The usability of the package and variance improvement, using this bootstrap methodology, is demonstrated on data from the user database (UDB) for the EU Statistics on Income and Living Conditions of selected countries with various sampling designs. © 2021 - IOS Press. All rights reserved.

关键词： bootstrapping Complex surveys r-programming resampling variance estimation

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Mapping cropland extent using sentinel-2 datasets and machine learning algorithms for an agriculture watershed

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SMArT AGrICULTUrAL TECHNOLOGY 2023年 4卷

作者： Savitha, Chirasmayee Talari, reshma NIT Andhra Pradesh Dept Civil Engn Tadepalligudem Andhra Pradesh India

Mapping and monitoring cropland extents are among the most appreciated element for resource management, monitoring, and assessment. India, being the most densely inhabited and agronomical country, mapping high -resolution cropland extent provides appreciated statistics and data for various resource management practices from an individual farm unit to larger administrative units. However, currently available cropland extent maps at global, continental, and regional extents are derived from coarser resolution satellite imageries. For smaller administrative unit with areas less than 10,000 Ha, these coarse resolution maps, often misclassify, resulting in uncertainties in accurate cropland accuracy. To overcome these limitations, in this study an effort is made to develop 10-m fine-resolution cropland extent maps using multi-temporal Sentinel-2 datasets for a watershed in Tadepalligudem, India. The selected study area is an agriculture dominant watershed covering an area of 5375 Ha. The satellite datasets used for the present study are selected with minimum cloud cover and are time-composited over three crop seasons (Kharif, rabi, and Zaid). With the successful advent of machine learning methods in remote sensing applications, cropland extent maps are derived using random Forest (rF) and Support Vector Machine (SVM) supervised machine learning algorithms in r-Studio, an r-programming inter-face. rF and SVM are CArT-based machine learning algorithms, where the performance of rF depends on the number of trees ("ntrees") and the number of sampled features ("mtry"), while for SVM it depends on Kernel functions used. To rejoice the need to develop a fine resolution, a comparative analysis is performed between 10-m resolution Sentinel-2 derived cropland extent maps and commonly used 30-m resolution Landsat-8 OLI-derived products. Training and testing samples collected from the field observations and high-resolution Google Earth Pro-is divided in a ratio of 75:25. In the prese

关键词： Cropland Machine learning r-programming random forest remote sensing Support vector machine

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Facilitating access to data on European Union laws

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POLITICAL rESEArCH EXCHANGE 2021年第1期3卷 Article: e1870150页

作者： Ovadek, Michal Katholieke Univ Leuven Ctr Empir Jurisprudence Leuven Belgium

Much of empirical research on European integration relies on data published by European Union (EU) institutions concerning the EU's laws and policies. However, despite wide disciplinary appeal and increasing regularization of data repositories such as Eur-Lex, researchers have so far not developed a standardized tool for accessing the main EU law databases. This research note presents the benefits of creating an open-source data collection infrastructure that takes advantage of the structured way in which data is published by the EU. I exemplify how software implementing this idea can be used by researchers.

关键词： Database r-programming European Union law and courts political methodology

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Detection and prevention of HIV AIDS Using Big Data Tool 3

Detection and prevention of HIV AIDS Using Big Data Tool

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3rd International Conference for Convergence in Technology (I2CT)

作者： Das, Nivedita Das, Leena rautaray, Siddharth Swarup Pandey, Manjusha Kalinga Inst Ind Technol Sch Comp Engn Bhubaneswar Orissa India

ISBN: (纸本)9781538642733

Big Data is an accumulation of data sets which are abundant and intricate in character. They comprise both structured and unstructured data that evolve abundant, so speedy they are not convenient by classical relational database systems or current analytical tools. Big Data Analytics is not linearly able to expand. It is a predefined schema. Big data analysis is the demanding one because it contains huge number of records. In today's world, the massive instruction about health care is to be prepared in order to recognize, diagnose, identify and prevent the various diseases. It is projected to develop a centralized patient monitoring system using big data. Health care is the conservation or advancement of health along the avoidance, interpretation and medical care of disorder, bad health, abuse, and other substantial and spiritual deterioration in mortal. One of the best areas where big data can be used to form an advance medical care. Medical care has the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general. Average human lifespan is increasing along world population, which poses new challenges to today's treatment delivery methods.. A disease is a particular abnormal condition that affects part or all of an organism not caused by external force and that consists of a disorder of a structure or function, usually serving as an evolutionary disadvantage. The study of disease is called pathology, which includes the study of cause. This paper mainly focuses on the prediction of disease like HIV/AIDS using r programming.

关键词： Predictive Analysis Big Data Tools Proposed framework r-programming

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Graph Database for recipe recommendations 7

Graph Database for Recipe Recommendations

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7th International Conference on reliability, Infocom Technologies and Optimization - Trends and Future Directions (ICrITO)

作者： Bajaj, Vasvi Panda, rajat Bhusan Dabas, Chetna Kaur, Parmeet Jaypee Inst Informat Technol Noida India

ISBN: (纸本)9781538646922

Graph databases represent a paradigm shift from relational databases with a strong support for "relationships". As compared to relational databases which compute relationships at runtime, graph databases persist relationships for fast querying and data retrieval. This work presents a recipe recommender as a graph database, Neo4j application. Given any set of ingredients, this application recommends a variety of recipes with the help of a data set containing thousands of ingredients. Further based on availability of ingredients with a user, this application helps discover the list of possible dishes with these ingredients. In order to implement this application, ingredients and recipes have been crawled from cookery based websites using Python scripts. The crawled data has been inserted into the Neo4j database and subsequently inter-relationships between ingredients and recipes nodes have been analyzed. Execution of self designed queries has verified the time-efficiency of the proposed approach.

关键词： GraphDB neo4j Food recipe clustering r-programming crawling

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