Investigation for utilization of training resources in technical education: A comparative study

This research study presents a comparative study between the quarter and the semester systems in the technical institutes, in terms of scheduling, training, and utilizing the training resources such as classrooms/halls capacity and employing the instructors. The size of the study sample was represented by the total number of students in classrooms/halls for the study courses in the quarter system by 8836 students distributed over 363 sections. While in the semester system 10360 students distributed over 358 sections. Thus, a comparison was made based on one training year between the two training systems for basic skills courses. The samples were used to know the effect of class capacity and teaching loads on the training system by making initial comparisons, and statistical tools were used where averages of class capacity and teaching loads were calculated to know the status and trends of the data using the plot box. In addition to descriptive statistics (Two samples F-test for variance) and finally, (t-test: Two samples assuming unequal variance) were selected. The p-value less than 0.05 of single-tailed confirmed that classroom capacity and instructors’ load were higher in the semester system compared to the quarter system.

Forgetting tracked by recognition of pictures

Thirty-three participants viewed 1,000 pictures for 6 s each. Recognition was tested after 10 different intervals of time by mixing 100 of the original 1,000 with 100 new pictures. Participants judged each test picture “Old” or “New” on a 6-point scale. The unequal-variance recognition model is reinterpreted to estimate the probability of retrieval of an original (1,000) picture after each lapse of time. A second model then relates those different estimates of accessibility to the lapse of time, taking into account the interference on each test from pictures presented in preceding tests. Studies of category judgement explain (a) why the model distributions are normal, (b) why the operating characteristics are asymmetric, (c) why they are curvilinear, and (d) why the asymmetry decreases with lapse of time, this to justify a particular estimate of accessibility (probability of retrieval). Nine candidate functions are shown to the accessibilities. The underlying relation is a power law, but the exponent is poorly determined by the data (−1.5, −0.5), as also is the offset from the temporal origin. Comparisons with previous work identify two different relationships with respect to lapse of time: The retrieval of a unique image shows an approximately reciprocal loss, whereas a decrease in the amount of material reproduced by recall, recognition, or other method is approximately logarithmic. The present experiment exhibits both relationships, depending on whether specific account is taken of the effects of interference or, alternatively, interference is entirely ignored.

Temporal deposition of copper and zinc in the sediments of metal removal constructed wetlands

The objective of this study was to explore the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments. This study was performed at the H-02 constructed wetland on the Savannah River Site (Aiken, SC, USA). Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the H-02 constructed wetland cells from 2007 to 2013. Total concentrations of Cu and Zn were measured in the sediments. Concentrations of Cu and Zn (mean ± standard deviation) in the surface sediments over 7 years of operation increased from 6.0 ± 2.8 and 14.6 ± 4.5 mg kg-1 to 139.6 ± 87.7 and 279.3 ± 202.9 mg kg-1 dry weight, respectively. The linear regression model explained the behavior and the variability of Cu deposition in the sediments. On the other hand, using the generalized least squares extension with the linear regression model allowed for unequal variance and thus produced a model that explained the variance properly, and as a result, was more successful in explaining the pattern of Zn deposition. Total carbon significantly affected both Cu (p = 0.047) and Zn (p < 0.001). Time effect on Cu deposition was statistically significant (p = 0.013), whereas Zn was significantly affected by the season (p = 0.009).

Bias effects in a two-stage recognition paradigm: A challenge for ‘pure’ threshold and signal detection models

We explored a two-stage recognition memory paradigm in which people first make single-item “studied”/“not studied” decisions and then have a chance to correct their errors in forced-choice trials. Each forced-choice trial included one studied word (“target”) and one non-studied word (“lure”) that received the same previous single-item response. For example, a “studied”-“studied” trial would have a target that was correctly called “studied” and a lure that was incorrectly called “studied.” The two-high-threshold (2HT) model and the unequal-variance signal detection (UVSD) model predict opposite effects of biasing the initial single-item responses on subsequent forced-choice accuracy. Results from two experiments showed that the bias effect is actually near zero and well out of the range of effects predicted by either model. Follow-up analyses showed that the model failures were not a function of experiment artifacts like changing memory states between the two types of recognition trials. Follow-up analyses also showed that the dual process signal detection (DPSD) model made better predictions for the forced-choice data than 2HT and UVSD models.

COMPARISON OF FINANCIAL PERFORMANCE OF GOVERNMENT BANKS AND NATIONAL PRIVATE BANKS IN BOOK CATEGORY 4

The purpose of this research is to compare empirically the performance of government banks and national private banks in the period of 2014-2019. The population in this study includes government-owned banks (BUMN) and national private banks (BUSN) registered in BUKU 4. The statistical method used has been t-test for different variants (unequal variance) with the separated variance formula. Data processing to compare the financial performance of government banks and national private has been based on the independent sample t-tests. The results show that there are differences when using several measuring instruments.

Evidence of misuse of nonparametric tests in the presence of heteroscedasticity within obesity research

Background: Classic nonparametric tests (cNPTs), like Kruskal–Wallis or Mann–Whitney U, are sometimes used to detect differences in central tendency (i.e., means or medians). However, when the tests’ assumptions are violated, such as in the presence of unequal variance and other forms of heteroscedasticity, they are no longer valid for testing differences in central tendency. Yet, sometimes researchers erroneously use cNPTs to account for heteroscedasticity. Objective: To document the appropriateness of cNPT use in obesity literature, characterize studies that use cNPTs, and evaluate the citation and public sharing patterns of these articles. Methods: We reviewed obesity studies published in 2017 to determine whether the authors used cNPTs: (1) to correct for heteroscedasticity (invalid); (2) when heteroscedasticity was clearly not present (correct); or (3) when it was unclear whether heteroscedasticity was present (unclear). Open science R packages were used to transparently search literature and extract data on how often papers with errors have been cited in academic literature, read in Mendeley, and disseminated in the media. Results: We identified nine studies that used a cNPT in the presence of heteroscedasticity (some because of the mistaken rationale that the test corrected for heteroscedasticity), 25 articles that did not explicitly state whether heteroscedasticity was present when a cNPT was used, and only four articles that appropriately reported that heteroscedasticity was not present when a cNPT was used. Errors were found in observational and interventional studies, in human and rodent studies, and only when studies were unregistered. Studies with errors have been cited 113 times, read in Mendeley 123 times, and disseminated in the media 41 times, by the public, scientists, science communicators, and doctors. Conclusions: Examples of inappropriate use of cNPTs exist in the obesity literature, and those articles perpetuate the errors via various audiences and dissemination platforms.

A Hierarchical Unequal-Variance Signal Detection Model for Binary Data

Gaussian signal detection models with equal variance are typically used for detection and discrimination data whereas models with unequal variance rely on data with multiple response categories or multiple conditions. Here a hier- archical signal detection model with unequal variance is suggested that requires only binary responses from a sample of participants. Introducing plausible constraints on the sampling distributions for sensitivity and response criterion makes it possible to estimate signal variance at the population level. This model was applied to existing data from memory and reasoning tasks and the results suggest that parameters can be reliably estimated, allowing a direct comparison of signal detection models with equal- and unequal-variance.

Irish Medical Laboratory Professionals and COVID-19: Response, Effect and Reflection on Future Practice

Background: The COVID-19 pandemic has had an unprecedented effect on healthcare staff across the globe. Medical laboratory professionals are central in the diagnosis and monitoring of treatment of most diseases, including COVID-19. The effects of the COVID-19 pandemic and previous pandemics have been examined for other healthcare professions, but there has been no study examining the effects of a pandemic, or any other healthcare emergency on medical laboratory professionals. Method: A voluntary, online survey of 37 closed and open questions for medical and healthcare scientists working in Ireland was conducted in May 2020. The survey examined the responses and effects of COVID-19 on medical laboratory professionals along with any lessons learned. Statistical significance was determined by two-tailed t-test (unequal variance). Results: There were 272 respondents, representing over 10% of the total workforce of Medical Scientists in Ireland. The respondents reflected all ages, grades, and disciplines in laboratories across Ireland and 87% of respondents reported a change to core working hours. Increasing workload complexity was reported by 70% of respondents. More than half of respondents reported increased work stress during the pandemic. The pandemic has also resulted in improved work-based solidarity. Approximately 90% of respondents were proud of their laboratory’s response to COVID-19, although degree of pride was significantly higher among managerial staff as were feelings of being appreciated, suggesting opportunity for further communication of praise. The study reports lessons learned thus far in the pandemic, including realisation of their service’s flexibility and adaptability, the necessity of collaboration and preparedness and the importance of their work.Conclusions: The respondents have identified challenges, including lack of career progression opportunities and under-utilisation of their professional skills, paucity of public knowledge of the roles undertaken in the laboratory and remuneration disparities, combined with concerns regarding retention of newly-qualified and other staff owing to alternative career opportunities.

Power formulas for mixed effects models with random slope and intercept comparing rate of change across groups

We have previously derived power calculation formulas for cohort studies and clinical trials using the longitudinal mixed effects model with random slopes and intercepts to compare rate of change across groups [Ard & Edland, Power calculations for clinical trials in Alzheimer’s disease. J Alzheim Dis 2011;21:369–77]. We here generalize these power formulas to accommodate 1) missing data due to study subject attrition common to longitudinal studies, 2) unequal sample size across groups, and 3) unequal variance parameters across groups. We demonstrate how these formulas can be used to power a future study even when the design of available pilot study data (i.e., number and interval between longitudinal observations) does not match the design of the planned future study. We demonstrate how differences in variance parameters across groups, typically overlooked in power calculations, can have a dramatic effect on statistical power. This is especially relevant to clinical trials, where changes over time in the treatment arm reflect background variability in progression observed in the placebo control arm plus variability in response to treatment, meaning that power calculations based only on the placebo arm covariance structure may be anticonservative. These more general power formulas are a useful resource for understanding the relative influence of these multiple factors on the efficiency of cohort studies and clinical trials, and for designing future trials under the random slopes and intercepts model.

RELATIONSHIP OF VERBAL IQ WITH PERFORMANCE IQ AND FULL SCALE IQ ALONG WITH ANATOMICAL CHARACTERISTICS

The connection between the complete brain size and general mental ability (GMA) was acknowledged universally. Connection between the performance intelligence quotient (PIQ) score and anatomical characteristics such as complete brain size, height, gender and weight are also narrated in many research papers. Very little study has been compiled to derive the relationship of verbal IQ (VIQ) with PIQ, full scale IQ (FSIQ) and anatomical characteristics. The current research report aims to develop the relationship of VIQ with the above mentioned variables. It is identified herein that VIQ is unequal variance random variable, and its mean is positively connected with FSIQ (P<0.0001), PIQ (P=0.1903), height (P= 0.0002), brain size (P=0.0181) and gender (P=0.0002), while it is negatively interrelated with the joint interaction effects of PIQ and height (PIQ*Height) (P<0.0001) and FSIQ*Gender (P<0.0001). Variance of VIQ is negatively interrelated with gender (P=0.0017), brain size (P=0.0040), height (P=0.0970), FSIQ*Gender (P=0.0032), while it is positively interrelated with PIQ (P=0.0321), Gender* Height (P=0.0322) and Gender*Brain size (P=0.0441). It is concluded herein that VIQ is higher for females with higher FSIQ, PIQ, larger brain size, longer height, and lower interaction effects of FSIQ*Gender and PIQ*Height.