scholarly journals Novel pedagogical tool for simultaneous learning of plane geometry and R programming

2018 ◽  
Vol 4 ◽  
pp. e25485 ◽  
Author(s):  
Álvaro Briz-Redón ◽  
Ángel Serrano-Aroca
Keyword(s):  
Programming Language ◽  
Undergraduate Students ◽  
R Package ◽  
Plane Geometry ◽  
Cost Ratio ◽  
Geometric Constructions ◽  
Pedagogical Tool ◽  
Benefit Cost Ratio ◽  
Wide Range ◽  
R Programming

Programming a computer is an activity that can be very beneficial to undergraduate students in terms of improving their mental capabilities, collaborative attitudes and levels of engagement in learning. Despite the initial difficulties that typically arise when learning to program, there are several well-known strategies to overcome them, providing a very high benefit-cost ratio to most of the students. Moreover, the use of a programming language usually raises the interest of students to learn any specific concept, which has caused that many teachers around the world employ a programming language as a learning environment to treat almost every possible topic. Particularly, mathematics can be taught and learnt while using a suitable programming language. The R programming language is endowed with a wide range of capabilities that allow its use to learn different kind of concepts while programming. Therefore, complex subjects such as mathematics could be learnt with the help of this powerful programming language. In addition, since the R language provides numerous graphical functions, it could be very useful to acquire simultaneously basic plane geometry and programming knowledge at the undergraduate level. This paper describes the LearnGeom R package, a novel pedagogical tool, which contains multiple functions to learn geometry in R at different levels of difficulty, from the most basic geometric objects to high-complexity geometric constructions, while developing numerous programming skills.

scholarly journals Evaluating Public Programs with Close Substitutes: The Case of Head Start*

2016 ◽  
Vol 131 (4) ◽  
pp. 1795-1848 ◽  
Author(s):  
Patrick Kline ◽  
Christopher R. Walters
Keyword(s):  
Head Start ◽  
Test Score ◽  
The United States ◽  
Cost Ratio ◽  
Public Programs ◽  
Benefit Cost Ratio ◽  
Wide Range ◽  
Fiscal Impacts ◽  
The Cost ◽  
Benefit Cost

Abstract We use data from the Head Start Impact Study (HSIS) to evaluate the cost-effectiveness of Head Start, the largest early childhood education program in the United States. Head Start draws roughly a third of its participants from competing preschool programs, many of which receive public funds. We show that accounting for the fiscal impacts of such program substitution pushes estimates of Head Start’s benefit-cost ratio well above one under a wide range of assumptions on the structure of the market for preschool services and the dollar value of test score gains. To parse the program’s test score impacts relative to home care and competing preschools, we selection-correct test scores in each care environment using excluded interactions between experimental assignments and household characteristics. We find that Head Start generates larger test score gains for children who would not otherwise attend preschool and for children who are less likely to participate in the program.

scholarly journals Developing codes for validation of PM10, PM2.5, and O3 datasets using R programming language

2019 ◽  
Author(s):  
Ramin Nabizadeh ◽  
Mostafa Hadei
Keyword(s):  
Air Pollution ◽  
Programming Language ◽  
Assessment Method ◽  
Daily Maximum ◽  
Data Handling ◽  
R Programming Language ◽  
Wide Range ◽  
Us Epa ◽  
R Programming ◽  
Pm 10

Introduction: The wide range of studies on air pollution requires accurate and reliable datasets. However, due to many reasons, the measured concentra-tions may be incomplete or biased. The development of an easy-to-use and reproducible exposure assessment method is required for researchers. There-fore, in this article, we describe and present a series of codes written in R Programming Language for data handling, validating and averaging of PM10, PM2.5, and O3 datasets.   Findings: These codes can be used in any types of air pollution studies that seek for PM and ozone concentrations that are indicator of real concentra-tions. We used and combined criteria from several guidelines proposed by US EPA and APHEKOM project to obtain an acceptable methodology. Separate   .csv files for PM 10, PM 2.5 and O3 should be prepared as input file. After the file was imported to the R Programming software, first, negative and zero values of concentrations within all the dataset will be removed. Then, only monitors will be selected that have at least 75% of hourly concentrations. Then, 24-h averages and daily maximum of 8-h moving averages will be calculated for PM and ozone, respectively. For output, the codes create two different sets of data. One contains the hourly concentrations of the interest pollutant (PM10, PM2.5, or O3) in valid stations and their average at city level. Another is the   final 24-h averages of city for PM10 and PM2.5 or the final daily maximum 8-h averages of city for O3. Conclusion: These validated codes use a reliable and valid methodology, and eliminate the possibility of wrong or mistaken data handling and averaging. The use of these codes are free and without any limitation, only after the cita-tion to this article.

scholarly journals Economics of Weed Control Methods in Transplanted Rice Fields in Mid-hill of Nepal

2020 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Robinson Adhikary ◽  
Bishnu Bilas Adhikari ◽  
Bishnu Prasad Kandel
Keyword(s):  
Weed Control ◽  
Computer Software ◽  
R Package ◽  
Cost Ratio ◽  
Block Designs ◽  
Control Methods ◽  
Benefit Cost Ratio ◽  
Transplanted Rice ◽  
Hand Weeding ◽  
Benefit Cost

To assess economic of different weed control methods on transplanted rice, a research was conducted at farmers’ fields, Bhanu-11, Rupakot, Nepal during the rainy season of 2017. The experiment was laid out using single factorial Randomized Complete Block Designs (RCBD) with three replications of ten treatments as one hand weeding at 21 Days After Transplanting (DAT) (T1); two hand weedings at 21 and 42 DAT (T2); three hand weedings at 21 42 & 63 DAT (T3); single conoweeding at 21 DAT (T4); double cono weedings at 21 &42 DAT (T5); triple cono weedings at 21, 42 &63 DAT (T6); butachlor as pre emergence (T7); butachlor with single manual weeding at 21 DAT (T8); butachlor with double manual weedings at 21 & 42 DAT (T9) and weedy check (T10). All collected data were subjected to analyzed by computer software R package. The results revealed that butachlor as pre-emergence (T7), showed that significantly higher gross return (Rs. 167.51thousand/ha), net profit (Rs. 96.11thousand/ha) and higher benefit-cost ratio (2.346), which is economically viable and profitable and can recommend to the farmers for rainfed lowland condition.

scholarly journals see: An R Package for Visualizing Statistical Models

2021 ◽  
Author(s):  
Daniel Lüdecke ◽  
Indrajeet Patil ◽  
Mattan S. Ben-Shachar ◽  
Brenton M. Wiernik ◽  
Philip Waggoner ◽  
...  
Keyword(s):  
Programming Language ◽  
Statistical Models ◽  
R Package ◽  
Model Parameters ◽  
R Programming Language ◽  
R Packages ◽  
R Programming ◽  
And Performance ◽  
Performance Diagnostics ◽  
Scientific Reporting

The see package is embedded in the easystats ecosystem, a collection of R packages that operate in synergy to provide a consistent and intuitive syntax when working with statistical models in the R programming language (R Core Team, 2021). Most easystats packages return comprehensive numeric summaries of model parameters and performance. The see package complements these numeric summaries with a host of functions and tools to produce a range of publication-ready visualizations for model parameters, predictions, and performance diagnostics. As a core pillar of easystats, the see package helps users to utilize visualization for more informative, communicable, and well-rounded scientific reporting.

scholarly journals neatStats: An R Package for a Neat Pipeline From Raw Data to Reportable Statistics in Psychological Science

2021 ◽  
Author(s):  
Gáspár Lukács
Keyword(s):  
Programming Language ◽  
R Package ◽  
Psychological Experiment ◽  
Raw Data ◽  
R Programming Language ◽  
Psychological Science ◽  
Data Files ◽  
R Programming

Performing the entire transition from raw data to reportable statistics can pose difficulties: it takes time, it allows various mistakes (that may or may not go unnoticed), and there are no general guidelines on how to proceed with this task. One particularly useful tool for this transition is the R programming language. However, how to use R for this is not trivial, especially for novices. The present paper serves as a step-by-step yet fast tutorial on how to make all the steps from raw data files to all the statistics normally needed in a conventional psychological experiment (including ANOVA and t-tests). At the same time, it also introduces the R package neatStats, which was created for the very purpose of making these steps as easy and straightforward as possible.

scholarly journals firebehavioR: An R Package for Fire Behavior and Danger Analysis

Fire ◽  
2019 ◽  
Vol 2 (3) ◽  
pp. 41
Author(s):  
Justin P. Ziegler ◽  
Chad M. Hoffman ◽  
William Mell
Keyword(s):  
Programming Language ◽  
Wildland Fire ◽  
Fire Behavior ◽  
R Package ◽  
Technical Note ◽  
Empirical Modeling ◽  
Behavior Modeling ◽  
Modeling Systems ◽  
R Programming ◽  
Data Objects

Wildland fire and ecological researchers use empirical and semi-empirical modeling systems to assess fire behavior and danger. This technical note describes the firebehavioR package, a porting of two fire behavior modeling systems, Crown Fire Initiation and Spread and a Rothermel-based framework, to the R programming language. We also highlight supporting data objects and functions to predict inputs required for fire behavior estimation. Last, this package contains functions for fifteen indices to express fire danger using weather and/or fuels observations. Specific advantages of predicting fire behavior using R, a free-and-open-source programming language, include freedom to adapt calculations to suit users’ needs, transparency of source code, and reduction of workflow inefficiencies, thereby aiding in sophisticated fire behavior analyses.

scholarly journals PRODUCTION AND MARKETING OF BANANA:

2019 ◽  
Vol 2 (1) ◽  
pp. 23-32
Author(s):  
M. B. Ranathilaka ◽  
Neluma Lashmi ◽  
Wasantha Atukorala
Keyword(s):  
Supply Chain ◽  
Sri Lanka ◽  
Value Chain ◽  
Cost Ratio ◽  
Banana Production ◽  
Benefit Cost Ratio ◽  
Sales Channels ◽  
Wide Range ◽  
Using Data ◽  
Benefit Cost

Banana is one of the prominent cultivation fruits in Sri Lanka and at present, approximately 54 percent of the total fruit cultivation lands are used to cultivate Banana. There is a wide range in cultivating practices and sales channels which all are linked together into the supply chain in the country. The domestic Banana supply chain is a good example of the fruit and vegetable supply chain of the country. This study attempts to determine the relative profitability of   banana using data collected from ‘Walawa region’ during the period of July to September 2017. Total cost, profit and benefit cost ratio for indifferent marketing channels such as banana producers, wholesalers and retailers ware investigated. The results show that, the profit margin of the retailer is greater than that of the farmers and wholesalers. It is also found that average benefit cost ratio of the producer has the highest, however the retailer has the largest impact on determining the price of banana in the intermediate chain. The results of this study can be used to make appropriate policies for increasing the competition in different value chain of the Banana production and marketing in Sri Lanka.

Read, Understand, Learn, & Excel: Development and Testing of an Automated Reading Strategy Detection Algorithm for Postsecondary Students

2019 ◽  
Vol 28 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Priya Kucheria ◽  
McKay Moore Sohlberg ◽  
Jason Prideaux ◽  
Stephen Fickas
Keyword(s):  
Academic Success ◽  
Undergraduate Students ◽  
Expository Text ◽  
Reading Strategy ◽  
Detection Algorithm ◽  
Expository Texts ◽  
Human Observer ◽  
Behavioral Strategies ◽  
Periodic Review ◽  
Wide Range

PurposeAn important predictor of postsecondary academic success is an individual's reading comprehension skills. Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader's use of strategies. The primary aim of this study was to develop Read, Understand, Learn, & Excel, an automated tool designed to detect reading strategy use and explore its accuracy in detecting strategies when students read digital, expository text.MethodAn iterative design was used to develop the computer algorithm for detecting 9 reading strategies. Twelve undergraduate students read 2 expository texts that were equated for length and complexity. A human observer documented the strategies employed by each reader, whereas the computer used digital sequences to detect the same strategies. Data were then coded and analyzed to determine agreement between the 2 sources of strategy detection (i.e., the computer and the observer).ResultsAgreement between the computer- and human-coded strategies was 75% or higher for 6 out of the 9 strategies. Only 3 out of the 9 strategies–previewing content, evaluating amount of remaining text, and periodic review and/or iterative summarizing–had less than 60% agreement.ConclusionRead, Understand, Learn, & Excel provides proof of concept that a reader's approach to engaging with academic text can be objectively and automatically captured. Clinical implications and suggestions to improve the sensitivity of the code are discussed.Supplemental Materialhttps://doi.org/10.23641/asha.8204786

Comparative Effectiveness Of Seed Treating And Foliar Insecticides Against Sucking Pests Of Cotton And Impact On Their Natural Enemies

2013 ◽  
Vol 38 (1) ◽  
pp. 61-70 ◽  
Author(s):  
SMA Hossain ◽  
MA Baque ◽  
MR Amin
Keyword(s):  
Natural Enemies ◽  
Untreated Control ◽  
Seed Treatment ◽  
Foliar Spray ◽  
Cost Ratio ◽  
Research Station ◽  
Benefit Cost Ratio ◽  
Benefit Cost ◽  
Thrips Population ◽  
Cotton Cultivar

The Imidacloprid insecticide, Gaucho 70 WS at 1.5, 2.5, 3.5, 4.5 and 5.5 g/kg seed was used as seed treatment and monocrotophos 40 WSC at 1120 ml/ha was applied as foliar spray on CB9 cotton cultivar to suppress aphid, whitefly and thrips, and impact on their natural enemies during 2008-2011 at the Regional Cotton Research Station, Dinajpur, Bangladesh. The activity of natural enemies, such as ladybird beetle, lacewing, syrphid, and spider population on the sucking pests attacking cotton cultivar CB9 and yield of cotton were recorded. Imidacloprid significantly reduced aphid, whitefly, and thrips population on cotton crops compared to untreated control or foliar spray of monocrotophos 40 WSC at 1120 ml/ha. Ladybird beetles, lacewings, syrphids, and spiders were abundant in the field but their population decreased in the treated plots compared to untreated control. The CB9 cotton cultivar produced significantly higher yield (1.73 t/ha) with a benefit cost ratio 12.47 when seeds were treated with Imidacloprid at 5.5 g/kg fuzzy seed. This study indicated that Imidacloprid (Gaucho 70 WS) used as a seed treatment may be suggested to the cotton growers for controlling sucking pests. Bangladesh J. Agril. Res. 38(1): 61-70, March 2013 DOI: http://dx.doi.org/10.3329/bjar.v38i1.15190

Effect of Sunflower Residues and Herbicide on Weed Suppression, Grain Yield and Economics of Transplanted Aman Rice

2020 ◽  
Vol 23 (1) ◽  
pp. 47-58
Author(s):  
SS Tanu ◽  
P Biswas ◽  
S Ahmed ◽  
SC Samanta
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Block Design ◽  
Weed Suppression ◽  
Cost Ratio ◽  
Gross Margin ◽  
Weed Density ◽  
Benefit Cost Ratio ◽  
Hand Weeding ◽  
Environmentally Sound

A field experiment was conducted at Agronomy Field Laboratory, Patuakhali Science and Technology University, Dumki, Patuakhali from July 2018 to November 2018 to evaluate the effect of sunflower residues and herbicides on the yield and economic performance of transplanted Aman rice. Weed control methods tested were T1 = weedy check (Unweeded control), T2 = Weed-free check by hand weeding twice, T3 = Pendimethalin, T4 = Pretilachlor, T5 = Butachlor, T6 = Pyrazosulfuron ethyl, T7 = Bensulfuron methyl + Acetachlor, T8 = Bispyriback sodium, T9 = 2,4-D amine, T10 = MCPA, T11 = Sunflower residues, T12 = Sunflower residues + 100% Pyrazosulfuron ethyl, T13 = Sunflower residues + 75% Pyrazosulfuron ethyl, T14 = Sunflower residues + 50% Pyrazosulfuron ethyl. The experiment was laid out in a randomized complete block design with fourteen treatments replicated thrice. Weedy check registered significantly the highest total weed density (354.67 m-2) and total weed dry matter (51.81 g-2) while weed-free treatment by hand weeding twice recorded significantly the lowest total weed density (6.67 m-2) and total weed dry matter 0.49 g-2) . Weedy check produced the highest weed index (34.24%) and hand weeding produced the lowest. Among different herbicides applied alone, butachlor had the lowest total weed density (15 m-2) and total weed dry matter (6.43 g-2) after hand weeding. Hand weeding recorded the highest grain yield (5.14 t ha-1) which was statistically similar to pendimethalin, pretilachlor, butachlor, bensulfuron methyl + acetachlor and sunflower residues + 100% pyrazosulfuron ethyl. Higher grain yield was attributed to a higher number of panicle m-2, number of filled grains panicle-1 and 1000-grain weight. The highest gross margin (22955 Tk. ha-1) and benefit-cost ratio (1.32) were obtained from butachlor. Integration of sunflower residues with pyrazosulfuron ethyl produced effective weed suppression and satisfactory yield comparable to butachlor. Although the integration is less profitable than butachlor the farmers can use this technology as a feasible and environmentally sound approach in transplanted Aman rice field. Bangladesh Agron. J. 2020, 23(1): 47-58

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