Statistical Covariance Research Articles

Kitchen Resources and Academic Achievements of Chemistry Students

This research work examined the use of kitchen resources in the teaching of Thermochemistry to SS1 Chemistry students in rural and urban schools. The sample was made up of 60 males and 40 females from two secondary schools in Ikom Local Government Areas in Cross River State, Nigeria. The design for the study was pre-test post-test control design. Chemistry Achievement Test (Cat) was used to collect data for the study Kinder Richardson Formula 21 was used to establish reliability of Cat. The reliability of Cat was 0.84. Analysis of covariance and descriptive statistics was used for data analysis. Findings showed a non-significant difference in relation to type of school environment and sex. It was recommended that teachers be innovative and resourceful using materials found at home to teach Chemistry concepts. This is so as type of school environment does not affect learning but materials used in teaching.

School Environment and Academic performance of SS1 Chemistry Students

This research work examined the use of home materials in the teaching of Thermochemistry to SS1 Chemistry students in rural and urban schools. Home materials like used ; fermentation fruit juices, heating capacities wood, induced thermal decomposition of shellfish shell powder and dissolution of glucose were used for the experiment. A total of 100 senior secondary one chemistry students were involved in the study. The sample was made up of 60 males and 40 females from two secondary schools in Ikom Local Government Areas in Cross River State, Nigeria. The design for the study was pre-test post-test control design. Chemistry Achievement Test (Cat) was used to collect data for the study Kinder Richardson Formula 21 was used to establish reliability of Cat. The reliability of Cat was 0.84. Analysis of covariance and descriptive statistics was used for data analysis. Findings showed a non-significant difference in relation to type of school environment and sex. It was recommended that teachers be innovative and resourceful using materials found at home to teach Chemistry concepts. This is so as type of school environment does not affect learning but materials used in teaching.

Energy consumption characteristics and adaptive electricity pricing strategies for college dormitories based on historical monitored data

College buildings, especially college dormitories, have a high density of energy consumption. It is important to obtain the energy consumption characteristics and impact factors of college dormitories before implementing energy efficiency measures. However, few studies based on experimental data have been reported. This study attempts to analyze the energy consumption characteristics of college dormitories and determine the influential factors based on monitored data. Annual daily energy consumption data of 480 college dormitories with different orientations and floors were collected. The energy consumption characteristics and the impact of factors including the floor, orientation, and occupant’s gender are investigated and quantified through the statistical methods and covariance analysis. The results show that the energy consumption varies significantly between different dormitories, and the floor location is the most influential factor. The annual energy consumption of the dormitories on the top floor is 10̃15% higher compared with those on the other floors due to higher cooling or heating load resulting from the roof. Then, two floor-oriented electricity pricing strategies are recommended to balance the different energy bills caused by different located floors of rooms. The electricity tariffs for rooms on the middle/top floors should be increased/decreased by 3.5%/10.3% in the proposed floor-based electricity tariff. This study would provide a basis for energy efficiency improvement and tariff optimization for college dormitories.

An efficient algorithm for computation of information matrix in phase-type fitting

Phase-type (PH) fitting is a technique to approximate any general distribution as a PH distribution, which is a probability distribution representing an absorbing time of a Markov chain. Since the PH distribution is described as a discrete- or continuous-time Markov chain (CTMC), the PH fitting can provide approximate Markov models to any non-exponential stochastic models. Thus, the PH fitting is helpful for model-based performance evaluation. On the other hand, from the statistical point of view, the PH fitting is categorized as parameter estimation from data. Some efficient PH fitting techniques are based on the maximum-likelihood principle. Therefore, it is crucial to evaluate statistical errors, i.e., the variance and covariance of estimators. In maximum-likelihood estimation, the Fisher information matrix is a well-known method to compute the variance and covariance of estimators, and is obtained as the second derivative of the log-likelihood function (LLF). In this article, we propose an algorithm for efficiently computing the Fisher information matrix in PH fitting. By applying the uniformization technique to a CTMC, we design the algorithm for computing the second derivatives of LLF in PH fitting.

Personalized Computer Support of Performance Rates and Education Process in High School: Case Study of Engineering Students

To date, the existing principles of a unified approach to schooling do not meet the requirements of a fundamental socio-economic transition characterized by personalization and customization of products and services that concern all areas, including education. The paradigm of education systems is being restructured in many countries towards a new approach of personalized learning that is adapted to students' needs, allows them to choose individual educational trajectories, and respects unique skills and qualities. The study aimed to determine the impact of personalization on the academic performance of engineering students in physics. The experiment on personalized student support was conducted during the academic year 2018-2019 at I.T. Trubilin Kuban State Agrarian University. The sample covered 78 students. The starting point of the research was the assessment of students' skills in mathematics, as the study of physics is based on mathematical analysis and interpretation. Test in physics and the criterion of alpha Kronbach (test reliability is determined with a coefficient of 0.87) were used as a toolkit for research. Besides, the statistical tools and covariance analysis of data processing were employed. The research was supported by the SPSS Statistics software package. According to the results obtained, higher post-test scores were recorded for students in the experimental group. The personalized learning has been found to have a significant impact on the academic performance of students. Those with low and medium ability in mathematics demonstrated higher growth in academic achievement than students with recorded high aptitude scores. A correlation between learning methods and mathematical skills to achieve high academic performance has been established. The influence of personalization in the learning process was determined to be moderately high (determinacy coefficient of 72.6%). The study is relevant for the development of constructive approaches that could help teachers improve their approach to learning and students improve academic achievements. The results may be of interest to researchers of educational technology, educators, and university administration management.

Investigating learners' engagement and science learning outcomes in different designs of participatory simulated games

AbstractThe purpose of this study was to investigate the affordances of participatory simulations by comparing students' models of engagement and science learning outcomes in a multi‐team participatory simulated game (MPSG) and a single‐team participatory simulated game (SPSG). Two versions of a mobile‐based game about marine fishery management were created. Participants were 105 seventh‐grade students in Taiwan. Research instruments included a Science Game Engagement questionnaire and a Marine Ecosystem and Sustainability Test. Students' interviews and classroom videos were also collected. Students' models of engagement were analyzed by using Partial Least Squares Structural Equation Modeling, and comparisons of subscales of engagement and learning outcomes were made by Analysis of Covariance statistics. The results showed that the students in the MPSG group had a higher level of behavioral engagement and better learning achievement than the students in the SPSG group did. Also, in exploring the interrelationships among the subscales of students' engagement, we found that, in the SPSG group, students' behavioral engagement was positively predicted by their emotional engagement, while in the MPSG group, it was positively predicted by their social engagement. In both groups, behavioral engagement predicted cognitive engagement. This finding was supported by the video data in that more interactions among the group members were observed in the MPSG group. This indicated that the multi‐agent, dynamic modeling in the MPSG may have shifted the quality of the learners' social interactions. The affordances of participatory simulated games are discussed, and future research directions are provided. Practitioner notesWhat is already known about this topic Participatory simulations allow users to participate in simulations by controlling one of the roles in the system which models real‐life settings. Dynamic modeling is an essential feature of participatory simulations that allows the learners to see the exact impact of their participation on changes in the system. Students who learned with the participatory simulations showed significantly better reasoning in concept building and fewer misconceptions than with conventional simulations. However learners can overly emphasize racing to win in multi‐agent participatory simulations and tasks in participatory simulations can be too challenging for some learners. What this paper adds We compared students' engagement models in two versions of a participatory game–a multi‐team participatory simulated game (MPSG) and a single‐team participatory simulated game (SPSG). We found that in the MPSG social engagement predicted behavioral engagement while in the SPSG students' emotional engagement played an important role. Students who participated in the MPSG had better performance in system thinking than the students in the SPSG. Implications for practice and/or policy Dynamic modeling is not only authentic for simulating certain scientific phenomena but also it offers the affordances of improving the quality of learners' social interactions. This should be taken into account in the future design of educational simulations. A multi‐team design of participatory simulation taking advantage of competition among teams and collaboration within teams can help students to learn complex phenomena.

Effect of circuit strength training programme on waist-to-hip ratio of college students

The purpose of this study is to examine the amount of fat stored around the hips and thighs (waist-to-hip ratio) of college students in Ikere Ekiti, Nigeria, after a 12-week circuit strength training programme. The study adopted randomised pre-test post-test control group research design. Simple random sampling technique and fish bowl method with replacement were used. Anthropometric tape was the instrument used for the pre-test post-test data collection on the waist, girth and gluteal (hip girth) of participants. The two hypotheses formulated were tested with analysis of covariance statistics at a significant level of 0.05. It was observed that the intervention programme prevented the storage of fat around the hips and thighs of the experimental group from increasing to the level of high disease risk ≥ 1.00 for men and ≥ 0.85 for women. The study identified circuit strength training programme as a recipe to ameliorate hypokinetic conditions.
 Keywords: Circuit strength training, resistance exercise, waist girth, waits-to-hip ratio.

Multiple representation-based chemistry learning textbook of colloid topic

This study aimed to describe the differences in students’ learning outcomes using the multiple representation-based chemistry learning textbook and the conventional chemistry learning textbook. This study was a quasi-experimental research. The population of this study was eight classes of Mathematics and Natural Sciences at SMAN 4 Denpasar Bali Indonesia. The samples were selected by cluster sampling technique to determine a control and an experimental group. Students in the control group were taught by the conventional chemistry learning textbook, while students in the experimental group were taught by the multiple representation-based chemistry learning textbook. The data in the study were students’ learning outcomes. These data were analyzed using the analysis of covariance statistics. Results of the study showed that there was a significant difference in learning outcomes between students taught by the multiple representation-based chemistry learning textbook and those taught by the conventional chemistry learning textbook. From the mean of learning outcome scores, it could be concluded that the students’ learning outcomes who were taught by the multiple representation-based chemistry learning textbook were better than those of the conventional chemistry learning textbook.

Doppler weather radar data assimilation at convective-allowing grid spacing for predicting an extreme weather event in Southern India

ABSTRACT Thunderstorms and heavy rainfall are the most devastating and dangerous weather phenomena over the tropical region. Southern Peninsula India in general and regions close to Western Ghats in particular are very prone to such severe weather activity. To improve the short-range forecasting of such extreme weather hazards, tremendous efforts are made to develop Doppler Weather Radar (DWR) network over Indian region for detection and continuous monitoring of weather activities. In this study, the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-Var) data assimilation system are used to evaluate the importance of the frequently available DWR observations at convective-allowing grid spacing for predicting an extreme weather event. Various assimilation experiments are performed using background error covariance statistics generated from the National Meteorological Center (NMC) method and Ensemble method, quality control in radial winds, and with/without Digital Filter Initialization (DFI) schemes for DWR data assimilation. Results suggest that with the assimilation of DWR observations, the WRF model is able to predict selected rainfall events with less temporal, spatial and intensity error. Moreover, synoptic conditions are more favourable after DWR assimilation. Due to lack of precise initial conditions, control experiments are not able to capture this extreme weather activity. Results suggest that better skill is seen when the DFI method is used in combination with ensemble background error covariance as compared to other experiments. The maximum rainfall prediction skill is enhanced with DWR data assimilation experiment with DFI method and ensemble background error covariance statistics.

Covariance-Map Imaging: A Powerful Tool for Chemical Dynamics Studies.

Over the past decade or so, the state-of-the-art in the field of chemical reaction dynamics has progressed from studies of few-atom systems to wide-ranging investigations into a variety of photoinduced and collision-induced processes in much larger molecules. Many of these studies are of direct relevance to a wide audience of chemists, spanning fields such as atmospheric chemistry, astrochemistry, synthetic chemistry, and chemical biology. Key to this work has been the technique of velocity-map imaging, which allows complete product scattering distributions to be recorded for the process of interest. Recent advances in camera technology have enabled the development of multimass velocity-map imaging, in which the scattering distributions of all reaction products can be recorded in a single measurement. In addition to the scattering distributions of individual reaction products, the data set now contains information on correlations between the scattering distributions of two or more fragments. These correlations can be revealed using the technique of statistical covariance, yielding an approach known as covariance-map imaging. This review will introduce the reader to covariance mapping and will describe various applications of the technique within the field of chemical dynamics. The underlying concepts will be illustrated through a series of simple simulations, before moving on to describe a number of recent experimental studies in which covariance mapping has been used to obtain mechanistic insight and information on molecular structure on the femtosecond time scale.

A Spectral Grouping and Attention-Driven Residual Dense Network for Hyperspectral Image Super-Resolution

Although unprecedented success has been achieved in convolutional neural network (CNN)-based super-resolution (SR) for natural images, hyperspectral image (HSI) SR without auxiliary high-resolution images remains a challenging task due to the high spectral dimensionality, where learning effective spatial and spectral representations is of great importance. In this article, we introduce a novel CNN-based HSI SR method, termed spectral grouping and attention-driven residual dense network (SGARDN) to facilitate the modeling of all spectral bands and focus on the exploration of spatial-spectral features. Considering the block characteristic of HSI, we employ group convolutions in and between groups composed of highly similar spectral bands at early stages to extract informative spatial features and avoid spectral disorder caused by normal convolution. To exploit spectral prior, a new spectral attention mechanism constructed by covariance statistics of features is designed to adaptively recalibrate features. We adapt the spectral attention for group convolutions to rescale grouping features with holistic spectral information. These two sequential operations called spectral grouping and integration module aim to extract effective shallow spatial-spectral features that are reused in the following layers. On the other hand, the residual dense block can better deal with spatial-spectral features by experimental comparison and hence is combined with the spectral attention to form a new basic building block for powerful feature expression and spectral correlation learning. The experimental results on synthesized and real-scenario HSIs demonstrate the feasibility and superiority of the proposed method over other state-of-the-art methods.

A link between synaptic plasticity and reorganization of brain activity in Parkinson's disease

The link between synaptic plasticity and reorganization of brain activity in health and disease remains a scientific challenge. We examined this question in Parkinson's disease (PD) where functional up-regulation of postsynaptic D2 receptors has been documented while its significance at the neural activity level has never been identified. We investigated cortico-subcortical plasticity in PD using the oculomotor system as a model to study reorganization of dopaminergic networks. This model is ideal because this system reorganizes due to frontal-to-parietal shifts in blood oxygen level-dependent (BOLD) activity. We tested the prediction that functional activation plasticity is associated with postsynaptic dopaminergic modifications by combining positron emission tomography/functional magnetic resonance imaging to investigate striatal postsynaptic reorganization of dopamine D2 receptors (using 11C-raclopride) and neural activation in PD. We used covariance (connectivity) statistics at molecular and functional levels to probe striato-cortical reorganization in PD in on/off medication states to show that functional and molecular forms of reorganization are related. D2 binding across regions defined by prosaccades showed increased molecular connectivity between both caudate/putamen and hyperactive parietal eye fields in PD in contrast with frontal eye fields in controls, in line with the shift model. Concerning antisaccades, parietal-striatal connectivity dominated in again in PD, unlike frontal regions. Concerning molecular-BOLD covariance, a striking sign reversal was observed: PD patients showed negative frontal-putamen functional-molecular associations, consistent with the reorganization shift, in contrast with the positive correlations observed in controls. Follow-up analysis in off-medication PD patients confirmed the negative BOLD-molecular correlation. These results provide a link among BOLD responses, striato-cortical synaptic reorganization, and neural plasticity in PD.

Effects of peer tutoring and study questions–based instructional strategies on students’ achievement and attitude towards mathematics in Bayelsa State, Nigeria

The purpose of the study was to examine the effects of peer tutoring and study questions - based instructional strategies on students’ achievement and attitude towards mathematics. The study was carried out on Bayelsa State public secondary schools mathematics students. Two research questions were raised and two corresponding null hypotheses that were tested at 0.05 level of significance guided the study. A pretest- posttest control group quasi-experimental design was employed. The study made use of two experimental groups and a control group. The purposive sampling technique was used to select 173 junior secondary class 3 (JS3) mathematics students from six mixed secondary schools. Mathematics Achievement Test (MAT) and Mathematics Students’ Attitude Questionnaire (MSAQ) were the two instruments used in the study. These instruments were validated using face validity, content validity and construct validity. All the research questions were answered with mean and standard deviation. Furthermore, all the null hypotheses were tested using analysis of covariance (ANCOVA) and Scheffe test statistics. One of the findings shows that peer tutoring and study questions - based instructional strategies were effective in the improvement of students’ achievement in mathematics. The findings indicated that peer tutoring and study questions - based instructional strategies have some relative positive impact on students’ attitude in mathematics. The researchers thus recommended that peer tutoring and study questions – based instructional strategies should be adopted by mathematics teachers as instructional strategies at the Junior Secondary School level in Bayelsa State.

Effect of the 7E Instructional Strategy on the Overall Attitude of Students in Biology in Public Secondary Schools in Adamawa State, Nigeria

The effect of attitude as a psychological construct that impacts students achievement in secondary schools have been widely reported, and the need to address that non-cognitive trait, so as to improve students’ achievement have been stressed. Negative attitude of students have adversely affected educational outcomes and the need to improve this trait in students is the aim of this study. The study investigated the effect of the 7E instructional strategy on the overall attitude of students of the 11th grade, in Biology, in public secondary schools in Adamawa State, Nigeria. Four attitude constructs, namely; attitude towards Biology as a subject; attitude towards the Biology teacher; perception of importance of Biology and perception of difficulty of Biology; were used in the study. Two randomly selected schools were denoted as experimental and control groups and were taught using the 7E instructional strategy and the teacher-centered methods, respectively. A 38-item Likert-based questionnaire was used to collect data before and after intervention was given. The research question was answered by the means and standard deviations, while the hypothesis was analysed using the Analysis of Covariance (ANCOVA) statistics. The descriptive statistics results showed that the experimental group had higher mean scores in three out of the four attitude variables, while no significant difference was recorded on one variable. The overall attitude of students taught by the 7E instructional strategy and when taught by traditional teacher-centered method, showed that students’ attitude is positively affected, by the 7E instructional strategy. Therefore, 7E instructional strategy significantly improved students’ attitude towards Biology.

Dual-centered ANCOVA: Resolving contradictory results from Lord's paradox with implications for reducing bias in longitudinal analyses

IntroductionValid causal inferences are necessary to use developmental research to improve adolescent outcomes. What type of change should be analyzed to approximate causal inferences from longitudinal data? Difference-score and ANCOVA-type analyses often produce contradictory results, a problem known as Lord's paradox. This study investigates 2-group, 2-wave difference-score analyses and ANCOVA, and introduces a method that produces consistent results, namely dual-centered ANCOVA, which is compared to pretest matching. MethodsThese methods are tested first on two datasets simulated to fit each of Lord's contrasting results. The methods are then applied to data investigating the longitudinal associations of parent-adolescent discussions about sexual risks on subsequent unprotected sexual behaviors in 4753 American adolescents (62.2% whites). ResultsThe results replicate Lord's contradictory results for all datasets. Dual-centered ANCOVA and pretest matching both produce consistent results, but dual-centered ANCOVA replicates the original results for difference-score analyses, whereas pretest matching replicates the original ANCOVA results. Thus, the two sets of consistent results differ from each other as much as the original discrepancy rather than reducing bias. ConclusionThe least biased analysis is the one whose null hypothesis best approximates a plausible change pattern to represent a no-treatment effect. When difference-score analyses are thought to approximate valid causal inferences as closely as ANCOVA-type analyses, dual-centered ANCOVA estimates the difference-score effect while retaining the advantages of ANCOVA in statistical power and covariate inclusion. These findings are widely applicable to longitudinal analyses that incorporate one or both of these basic methods to analyze change.

Spatial and spatio-temporal methods for mapping malaria risk: a systematic review

BackgroundApproaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of...

On One Statistical Model of Error Rate in the Stream of Packet Data Transmission through Communication Channels

A statistical model of the frequency of errors in the packet data transmission through communication channels is proposed. This is a stochastic sequence defined as the averaged proportion of erroneous data packets. A diffusion approximation of such a sequence is used: discrete Markov diffusion, which is defined by a difference stochastic equation. The parameters of such a model are estimated using covariance statistics on the trajectories of the stochastic sequence of signal transmission errors.

Appraising Minimum Effect of Standardized Contrasts in ANCOVA Designs: Statistical Power, Sample Size, and Covariate Imbalance Considerations

The concepts and implementation of standardized mean differences and minimum effect tests have been emphasized in ANOVA. The corresponding processes and implications are, however, not yet well explicated in the context of ANCOVA. To enhance the usefulness of ANCOVA, this article describes the minimum effect tests of standardized contrast as a valuable alternative to the hypothesis testing of no effect difference and the conventional evaluation of unstandardized effects in ANCOVA. Power and sample size procedures are developed to accommodate covariate randomness and imbalance for randomized and nonrandomized designs. The data from a clinical study of comparing two treatments for gingivitis are used to illustrate the application of the suggested approaches. The emphases of numerical appraisal are on the merit of minimum effect detection in comparative analysis and the influence of covariate feature in power and sample size computation. The proposed power and sample size calculations improve upon approximate formulas by fully accounting for the stochastic property and intrinsic disparity of the covariate variables. Computer algorithms are available for calculating the p-value, power level, and sample size of one- and two-sided minimum effect tests.

Recurrence relations for moments of order statistics from half logistic-geometric distribution and their applications

The half logistic-geometric (HLG) distribution derived here is a simple distribution with interesting properties and is therefore a useful distribution for analyzing lifetime data. Algorithm is derived for the computation of single and product moments of order statistics from this distribution. These recurrence relations enable the computation of means, variances and covariances of all order statistics for all sample size in a simple and efficient way. The results are of great importance in determining the best linear unbiased estimator of the scale parameter of a scaled-HLG distribution, and those of parameters of the more general location-scale HLG distribution based on complete and Type-II censored samples. Finally, an example is presented to illustrate the developed results.

Relationship quality and 5-year mortality risk.

The present study examined positive and negative aspects of relationship quality with one's spouse or partner as predictors of mortality and the role of gender in moderating this link. Data were drawn from 2 waves, 5 years apart, of the National Social Life, Health, and Aging Project (N = 1,734). Positive aspects of relationship quality (frequency of opening up to the partner to talk about worries and relying on the partner) and negative aspects (frequency of the partner making too many demands and criticism by the partner) were assessed. Survival/mortality status was recorded at the time of Wave 2 data collection 5 years later (1,567 alive; 167 deceased). Covariates included sociodemographic variables, relationship type, health status, and the network size of close family relationships and friendships. Logistic regression analyses showed that negative relationship quality with one's spouse or partner was associated with significantly higher odds for mortality after 5 years (odds ratio [OR] = 1.20, 95% CI [1.03, 1.38], p < .001), after including the statistical covariates. Also, age, gender, education, self-rated health, and medication use were significantly related to mortality. Propensity score matching replicated these findings. Follow-up analyses revealed that criticism from one's spouse or partner, in particular, was linked to a higher mortality risk (OR = 1.44, 95% CI [1.10, 1.88]). Gender did not moderate the relationship-quality-mortality link. Negative relationship quality, notably, criticism received from one's spouse or partner, heightens older adults' risk of mortality. These results suggest the value of developing interventions that target reducing expressed criticism in couple relationships. (PsycInfo Database Record (c) 2020 APA, all rights reserved).