This study aims to establish a rationale for the Rice University rule in determining the number of bins in a histogram. It is grounded in the Scott and Freedman-Diaconis rules. Additionally, the accuracy of the empiri...This study aims to establish a rationale for the Rice University rule in determining the number of bins in a histogram. It is grounded in the Scott and Freedman-Diaconis rules. Additionally, the accuracy of the empirical histogram in reproducing the shape of the distribution is assessed with respect to three factors: the rule for determining the number of bins (square root, Sturges, Doane, Scott, Freedman-Diaconis, and Rice University), sample size, and distribution type. Three measures are utilized: the average distance between empirical and theoretical histograms, the level of recognition by an expert judge, and the accuracy index, which is composed of the two aforementioned measures. Mean comparisons are conducted with aligned rank transformation analysis of variance for three fixed-effects factors: sample size (20, 35, 50, 100, 200, 500, and 1000), distribution type (10 types), and empirical rule to determine the number of bins (6 rules). From the accuracy index, Rice’s rule improves with increasing sample size and is independent of distribution type. It outperforms the Friedman-Diaconis rule but falls short of Scott’s rule, except with the arcsine distribution. Its profile of means resembles the square root rule concerning distributions and Doane’s rule concerning sample sizes. These profiles differ from those of the Scott and Friedman-Diaconis rules, which resemble each other. Among the seven rules, Scott’s rule stands out in terms of accuracy, except for the arcsine distribution, and the square root rule is the least accurate.展开更多
Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, th...Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.展开更多
The objective of this article is to demonstrate with examples that the two-sided tie correction does not work well. This correction was developed by Cureton so that Kendall’s tau-type and Spearman’s rho-type formula...The objective of this article is to demonstrate with examples that the two-sided tie correction does not work well. This correction was developed by Cureton so that Kendall’s tau-type and Spearman’s rho-type formulas for rank-biserial correlation yield the same result when ties are present. However, a correction based on the bracket ties achieves the desired goal, which is demonstrated algebraically and checked with three examples. On the one hand, the 10-element random sample given by Cureton, in which the two-sided tie correction performs well, is taken up. On the other hand, two other examples are given, one with a 7-element random sample and the other with a clinical random sample of 31 participants, in which the two-sided tie correction does not work, but the new correction does. It is concluded that the new corrected formulas coincide with Goodman-Kruskal’s gamma as compared to Glass’ formula that matches Somers’ d<sub>Y</sub><sub>|X</sub> or asymmetric measure of association of Y ranking with respect to X dichotomy. The use of this underreported coefficient is suggested, which is very easy to calculate from its equivalence with Kruskal-Wallis’ gamma and Somers’ d<sub>Y</sub><sub>|X</sub>.展开更多
The major offshoot of innovation of electric vehicles (EVs) is sustainability. Given the prevailing challenges of carbon emissions from automobiles and the consequent effects on climate change, the introduction of EVs...The major offshoot of innovation of electric vehicles (EVs) is sustainability. Given the prevailing challenges of carbon emissions from automobiles and the consequent effects on climate change, the introduction of EVs is timely to serve as an effective mechanism for reversing global warming. However, knowledge of EVs is not well distributed among the general population. This study is therefore aimed to analyze the familiarity of Americans with the basic features of EVs. One hundred respondents were selected from two underserved communities in Huntsville, Alabama, using a simple sampling technique. Nonetheless, only 71 residents returned the filled questionnaires. Data were analyzed using frequency counts and descriptive statistics. Findings revealed that the respondents were generally aware of EVs, but EVs are not yet common on their roads. The respondents also signaled low preferences for EVs. The purchase price, charging stations, and limited supply are the candid explanations for why EVs are not a priority in the respondents’ choice of cars. To bolster peoples’ taste toward EVs, the study, therefore, concludes that government authorities and city planners should popularize incentives among the people in underserved communities.展开更多
文摘This study aims to establish a rationale for the Rice University rule in determining the number of bins in a histogram. It is grounded in the Scott and Freedman-Diaconis rules. Additionally, the accuracy of the empirical histogram in reproducing the shape of the distribution is assessed with respect to three factors: the rule for determining the number of bins (square root, Sturges, Doane, Scott, Freedman-Diaconis, and Rice University), sample size, and distribution type. Three measures are utilized: the average distance between empirical and theoretical histograms, the level of recognition by an expert judge, and the accuracy index, which is composed of the two aforementioned measures. Mean comparisons are conducted with aligned rank transformation analysis of variance for three fixed-effects factors: sample size (20, 35, 50, 100, 200, 500, and 1000), distribution type (10 types), and empirical rule to determine the number of bins (6 rules). From the accuracy index, Rice’s rule improves with increasing sample size and is independent of distribution type. It outperforms the Friedman-Diaconis rule but falls short of Scott’s rule, except with the arcsine distribution. Its profile of means resembles the square root rule concerning distributions and Doane’s rule concerning sample sizes. These profiles differ from those of the Scott and Friedman-Diaconis rules, which resemble each other. Among the seven rules, Scott’s rule stands out in terms of accuracy, except for the arcsine distribution, and the square root rule is the least accurate.
文摘Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.
文摘The objective of this article is to demonstrate with examples that the two-sided tie correction does not work well. This correction was developed by Cureton so that Kendall’s tau-type and Spearman’s rho-type formulas for rank-biserial correlation yield the same result when ties are present. However, a correction based on the bracket ties achieves the desired goal, which is demonstrated algebraically and checked with three examples. On the one hand, the 10-element random sample given by Cureton, in which the two-sided tie correction performs well, is taken up. On the other hand, two other examples are given, one with a 7-element random sample and the other with a clinical random sample of 31 participants, in which the two-sided tie correction does not work, but the new correction does. It is concluded that the new corrected formulas coincide with Goodman-Kruskal’s gamma as compared to Glass’ formula that matches Somers’ d<sub>Y</sub><sub>|X</sub> or asymmetric measure of association of Y ranking with respect to X dichotomy. The use of this underreported coefficient is suggested, which is very easy to calculate from its equivalence with Kruskal-Wallis’ gamma and Somers’ d<sub>Y</sub><sub>|X</sub>.
文摘The major offshoot of innovation of electric vehicles (EVs) is sustainability. Given the prevailing challenges of carbon emissions from automobiles and the consequent effects on climate change, the introduction of EVs is timely to serve as an effective mechanism for reversing global warming. However, knowledge of EVs is not well distributed among the general population. This study is therefore aimed to analyze the familiarity of Americans with the basic features of EVs. One hundred respondents were selected from two underserved communities in Huntsville, Alabama, using a simple sampling technique. Nonetheless, only 71 residents returned the filled questionnaires. Data were analyzed using frequency counts and descriptive statistics. Findings revealed that the respondents were generally aware of EVs, but EVs are not yet common on their roads. The respondents also signaled low preferences for EVs. The purchase price, charging stations, and limited supply are the candid explanations for why EVs are not a priority in the respondents’ choice of cars. To bolster peoples’ taste toward EVs, the study, therefore, concludes that government authorities and city planners should popularize incentives among the people in underserved communities.
