scholarly journals Prediction of Heart Disease and Diabetes Using Naive Bayes Algorithm

2021 ◽  
pp. 447-453
Author(s):  
Ninad Marathe ◽  
Sushopti Gawade ◽  
Adarsh Kanekar
Keyword(s):  
Heart Disease ◽  
Potential Problem ◽  
University Of California ◽  
Test Report ◽  
Ui Design ◽  
R Programming Language ◽  
R Shiny ◽  
R Programming ◽  
Bayes Algorithm ◽  
The University

Based on the test report values, diagnose a potential problem. The patient's report can be entered as feedback by the doctors (Sugar level, Age, Blood pressure, etc.). Through evaluating the available data collection, we can predict whether the patient has heart disease or diabetes using the method. Apart from that, we use Rstudio's R shiny addon for Web UI design. As a coding language, we use the R programming language. The Rstudio IDE was used. The datasets were obtained from the University of California at Irvine's repository.

scholarly journals Creating statistics e-assessments using Dewis with embedded R code

2017 ◽  
Vol 15 (2) ◽  
pp. 51
Author(s):  
Iain Weir ◽  
Rhys Gwynllyw ◽  
Karen Henderson
Keyword(s):  
Learning Experience ◽  
Assessment System ◽  
Data Sets ◽  
Learning Modules ◽  
R Programming Language ◽  
E Learning ◽  
The Creation ◽  
R Programming ◽  
The Uk ◽  
The University

We report on the creation of statistics e-assessments using the Dewis system with embedded R code. Dewis is a fully algorithmic open-source e-assessment system designed and developed at the University of the West of England, Bristol (UWE). Dewis’ ability to communicate with the R programming language greatly facilitates the task of generating bespoke data and its subsequent analysis. This approach has allowed us to successfully test students’ ability to perform involved statistical analyses on individual data sets and led to the creation of a suite of open access online e-learning modules on the UK national statstutor website. Development of a Dewis-R interface allows the creation of sophisticated e-assessments solely by writing an R script file. The goal is to create a community of Dewis-R practitioners who will be able to author and share relevant, authentic and engaging statistics e-assessments that enrich the learning experience of students.

scholarly journals Reflections from Transitioning Carpentries Workshops Online

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Ben B. Chiewphasa ◽  
Anna K. Moeller
Keyword(s):  
Formative Assessments ◽  
Online Delivery ◽  
Face To Face ◽  
R Programming Language ◽  
Online Setting ◽  
R Programming ◽  
The Many ◽  
Interactive Workshop ◽  
The University ◽  
First Time

Objectives: As certified Carpentries instructors, the authors organized and co-taught the University of Montana’s first in-person Carpentries workshop focused on the R programming language during early 2020. Due to the COVID-19 pandemic, a repeated workshop was postponed to the fall of 2020 and was adapted for a fully online setting. The authors share their Carpentries journey from in-person to online instruction, hoping to inspire those interested in organizing Carpentries at their institution for the first time and those interested in improving their existing Carpentries presence. Methods: The authors reflected on their experience facilitating the same Carpentries workshop in-person and online. They used this unique opportunity to compare the effectiveness of a face-to-face environment versus a virtual modality for delivering an interactive workshop. Results: When teaching in the online setting, the authors learned to emphasize the basics, create many opportunities for feedback using formative assessments, reduce the amount of material presented, and include helpers who are familiar with technology and troubleshooting. Conclusions: Although the online environment came with challenges (i.e., Zoom logistics and challenges, the need to further condense curricula, etc.), the instructors were surprised at the many advantages of hosting an online workshop. With some adaptations, Carpentries workshops work well in online delivery.

scholarly journals An Intelligent Data-Driven Analytics System for Operation Management, Budgeting, and Resource Allocation using Machine Learning and Data Analytics

2021 ◽  
Author(s):  
Dele Fei ◽  
Yu Sun
Keyword(s):  
Data Analytics ◽  
Data Science ◽  
Forecast Model ◽  
Data Driven ◽  
R Programming Language ◽  
R Shiny ◽  
Customer Type ◽  
Web App ◽  
R Programming ◽  
Product Warranty

This is a data science project for a manufacturing company in China [1]. The task was to forecast the likelihood that each product would need repair or service by a technician in order to forecast how often the products would need to be serviced after they were installed. That forecast could then be used to estimate the correct price for selling a product warranty [2]. The underlying forecast model in the R Programming language for all of the companies products is established. In addition, an interactive web app using R Shiny is developed so the business could see the forecast and recommended warranty price for each of their products and customer types [3]. The user can select a product and customer type and input the number of products and the web app displays charts and tables that show the probability of the product needing service over time, the forecasted costs of service, along with potential income and the recommended warranty price.

scholarly journals Membuat Berbagai Grafik dengan STATCAL-VISUALIZATION

2018 ◽  
Author(s):  
Prana Ugiana Gio ◽  
Rezzy Eko Caraka ◽  
Dian utami sutiksno ◽  
Ansari Saleh Ahmar
Keyword(s):  
Programming Language ◽  
Application Program ◽  
R Programming Language ◽  
R Shiny ◽  
Program Application ◽  
R Programming

STATCAL-VISUALIZATION is a application program designed to make various graph easily. STATCAL-VISUALIZATION is designed using r programming language, in RStudio, with r shiny package as the main package. STACAL-VISUALIZATION program application can be downloaded in www.statcal.com.

STATISTICAL CALCULATOR

2018 ◽  
Author(s):  
Prana Ugiana Gio ◽  
Rezzy Eko Caraka
Keyword(s):  
R Package ◽  
Process Data ◽  
Web Based ◽  
Application Program ◽  
R Programming Language ◽  
Statistical Application ◽  
R Shiny ◽  
R Packages ◽  
R Programming ◽  
Mozilla Firefox

STATCAL is an free statistical application program that is designed using R programming language, in RStudio. STATCAL uses various R packages to perform graphical and statistical analysis. STATCAL is a web-based statistical application program. It means that STATCAL uses a browser, such as Google Chrome, Mozilla Firefox, etc, as a place or media to process data. R shiny package is a main package in STATCAL. R shiny package is an R package that can be used to create an interactive web-based application. STATCAL is created by Prana Ugiana Gio and Rezzy Eko Caraka on 2017.

scholarly journals Timing and Mode of Delivery in Prenatally Diagnosed Congenital Heart Disease- an Analysis of Practices within the University of California Fetal Consortium (UCfC)

2017 ◽  
Vol 38 (3) ◽  
pp. 588-595 ◽  
Author(s):  
Shabnam Peyvandi ◽  
◽  
Tina Ahn Thu Thi Nguyen ◽  
Myriam Almeida-Jones ◽  
Nina Boe ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Mode Of Delivery ◽  
University Of California ◽  
The University

scholarly journals An Academic Performance Indicator Using Flexible Multi-Criteria Methods

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2396
Author(s):  
Olga Blasco-Blasco ◽  
Marina Liern-García ◽  
Aarón López-García ◽  
Sandra E. Parada-Rico
Keyword(s):  
Academic Performance ◽  
Performance Indicator ◽  
First Year ◽  
First Semester ◽  
R Programming Language ◽  
Recent Method ◽  
Overall Performance ◽  
Support Policy ◽  
R Programming ◽  
The University

Composite indicators are a very useful tool for conveying summary information on the overall performance of institutions and facilitating decision-making. Increasingly, there is a demand for indicators that allow performance to be assessed after the implementation of a strategy. This has several difficulties, and in this paper, we address three of them: how to evaluate at different points in time, how to estimate the weighting of the criteria and how to normalize the data. Our proposal is based on multicriteria techniques, using a recent method, uwTOPSIS, and is applied to data collected from 2975 students enrolled in the first year of science and engineering at the Industrial University of Santander (Colombia) from the first semester of 2016 to the first semester of 2019. In the paper, we show that our proposal makes it possible to measure and evaluate the academic performance of students at two points in time, and this allows the University to know whether its student support policy has been successful and to what degree it has been effective. Due to the large amount of data handled, data management has been done using R programming language, and model implementation has been done with Python.

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