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.

Investigation of centrality dependence of dynamical fluctuations in narrow pseudo-rapidity interval on event-by-event basis

A detailed study of centrality dependence of event-by-event fluctuations of maximum particle density of the produced particles in narrow pseudo-rapidity interval in terms of the scaled variance [Formula: see text] has been carried out for [Formula: see text]O-emulsion interactions at 4.5[Formula: see text]AGeV/[Formula: see text]. Depending on the values of the total charges or sum of the charges of noninteracting projectile fragments, event samples were classified into four centrality classes. Presence of event-by-event fluctuations of maximum particle density is reflected in the multiparticle production process for different centrality classes. The event-by-event fluctuations are found to decrease with the increase of pseudo-rapidity interval. The event-by-event fluctuations are found to decrease with decreasing centrality of collisions. A comparison with the analyzed results of the total disintegration events has also been carried out. Experimental analysis results have been compared with those obtained from the analysis of Monte Carlo simulated (MC-RAND) events in order to extract the dynamical fluctuations.

Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods

A major open question, affecting the policy makers decisions, is the estimation of the true size of COVID-19 infections. Most of them are undetected, because of a large number of asymptomatic cases. We provide an efficient, easy to compute and robust lower bound estimator for the number of undetected cases. A “modified” version of the Chao estimator is proposed, based on the cumulative time-series distribution of cases and deaths. Heterogeneity has been accounted for by assuming a geometrical distribution underlying the data generation process. An (approximated) analytical variance formula has been properly derived to compute reliable confidence intervals at 95%. An application to Austrian situation is provided and results from other European Countries are mentioned in the discussion.

On the Exact Variance of Tsallis Entanglement Entropy in a Random Pure State

The Tsallis entropy is a useful one-parameter generalization to the standard von Neumann entropy in quantum information theory. In this work, we study the variance of the Tsallis entropy of bipartite quantum systems in a random pure state. The main result is an exact variance formula of the Tsallis entropy that involves finite sums of some terminating hypergeometric functions. In the special cases of quadratic entropy and small subsystem dimensions, the main result is further simplified to explicit variance expressions. As a byproduct, we find an independent proof of the recently proven variance formula of the von Neumann entropy based on the derived moment relation to the Tsallis entropy.

Indices of Subscore Utility for Individuals and Subgroups Based on Multivariate Generalizability Theory

Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [Formula: see text], which quantifies the ratio of true score profile variance to observed score profile variance. [Formula: see text] has been shown to be more sensitive than correlational methods to group differences in score profile utility. However, it is a group average, representing the expected value over a population of examinees. Just as score reliability varies across individuals and subgroups, one can expect that the reliability of score profiles will vary across examinees. This article proposes two conditional indices of score profile utility grounded in multivariate generalizability theory. The first is based on the ratio of observed profile variance to the profile variance that can be attributed to random error. The second quantifies the proportion of observed variability in a score profile that can be attributed to true score profile variance. The article describes the indices, illustrates their use with two empirical examples, and evaluates their properties with simulated data. The results suggest that the proposed estimators of profile error variance are consistent with the known error in simulated score profiles and that they provide information beyond that provided by traditional measures of subscore utility. The simulation study suggests that artificially large values of the indices could occur for about 5% to 8% of examinees. The article concludes by suggesting possible applications of the indices and discusses avenues for further research.

The Influence of Causal Thinking with Scaffolding Type 2A and 2B on Optics Problem-Solving Ability

The effectiveness of learning is affected by the assistance stages (scaffolding) provided. For example, the scaffolding of type 2a and type 2b supports the causal-thinking approach in learning. The type 2a informs the causal model, number of causes and effect, while 2b informs its argument sample. This research aimed to identify the effect of causal thinking process (CTP) with scaffolding type 2a and 2b on optics problem-solving ability (PSA) of students. The type of the research was quasi-experiment with the non-equivalent-group design. Data were obtained with PSA-test and analyzed with the two-tail test with separated variance formula at significance degree of 5% to determine the effect of each type of the CTP on the PSA, also to determine its difference. The results showed that tcount for each of the first two t-tests were greater than ttable, but tcount for the third one was smaller than its ttable. This research concluded that the implementation of the CTP with the scaffolding of type-2a and 2b were effective to improve the student’s PSA. However, the improvements were not different.Efektivitas pembelajaran dipengaruhi bantuan tahapan (scaffolding) yang diberikan. Dengan pendekatan berpikir kausalitik ini, diperkenalkan scaffolding tipe-2a dan tipe-2b. Kedua scaffolding ini menginformasikan model kausal serta jumlah Cause dan Effect tetapi pada tipe-2b ditambah contoh argumentasinya. Penelitian ini bertujuan mengidentifikasi pengaruh proses-berpikir-kausalitik (PBK) ber-scaffolding tipe-2a dan tipe-2b terhadap kemampuan-pemecahan-masalah (KPM) optik siswa. Jenis penelitian kuasi-eksperimen dengan desain non-equivalent-group. Data diambil menggunakan alat tes-KPM dan dianalisis dengan uji-t dua pihak menggunakan rumus separated varians pada signifikansi 5% untuk mengetahui pengaruh PBK tipe-2a dan 2b terhadap KPM, serta perbedaan kedua pengaruh tersebut. Hasil menunjukkan nilai thitung untuk dua uji-t pertama lebih besar dari tTable terkait tetapi nilai thitung untuk uji ketiga adalah lebih kecil dari tTable-nya. Simpulan penelitian implementasi PBK ber-scaffolding tipe-2a dan 2b masing-masing berpengaruh terhadap peningkatan KPM siswa tetapi kedua pengaruh tersebut tidak berbeda.

Conditional Precision of Measurement for Test Scores: Are Conditional Standard Errors Sufficient?

This inquiry is focused on three indicators of the precision of measurement—conditional on fixed values of θ, the latent variable of item response theory (IRT). The indicators that are compared are (1) The traditional, conditional standard errors, [Formula: see text] = CSEM; (2) the IRT-based conditional standard errors, [Formula: see text] (where [Formula: see text] is the IRT score information function); and (3) a new conditional reliability coefficient, [Formula: see text]. These indicators of conditional precision are shown to be functionally related to one another. The IRT-based, conditional CSEM, [Formula: see text], and the conditional reliability, [Formula: see text], involve an estimate of the conditional true variance, [Formula: see text], which is shown to be approximately equal to the numerator of the score information function. It is argued—and illustrated with an example—that the traditional, conditional standard error, CSEM, is not sufficient for determining conditional score precision when used as the lone indicator of precision; hence, the portions of a score distribution, where scores are most-and-least precise, can be misidentified.

Largest eigenvalue of large random block matrices: A combinatorial approach

We study the largest eigenvalue of certain block matrices where the number of blocks and the block size both increase with suitable conditions on their relative growth. In one of them, we employ a symmetric block structure with large independent Wigner blocks and in the other we have the Wigner block structure with large independent symmetric blocks. The entries are assumed to be independent and identically distributed with mean [Formula: see text] variance [Formula: see text] with an appropriate growth condition on the moments. Under our conditions the limit spectral distribution of these matrices is the standard semi-circle law. It is natural to ask if the extreme eigenvalues converge to the extreme points of its support, namely [Formula: see text]. We exhibit models where this indeed happens as well as models where the spectral norm converges to [Formula: see text]. Our proofs are based on combinatorial analysis of the behavior of the trace of large powers of the matrix.

Twinning Rates in Isolates

The aim of this study was to investigate the twinning rates (TWRs) in isolates relative to the TWRs in the surrounding populations. It is not uncommon that the TWR shows extreme values (high or low rates) within isolated subpopulations. Starting from the isolated populations of the Åland Islands in Finland (high rates), we enlarged our studies to other isolated subpopulations in other countries: the island of Gotland (high rates), the county of Älvsborg located in the southwestern part of Sweden (low rates), and mountain villages in Norway. In our statistical analyses, we paid special attention to the robustness of the variance formula of the TWR and to alternative confidence intervals for the TWR. Particularly, we show how to obtain the most precise confidence intervals for the twinning rates. These statistical methods are crucial when the extreme TWRs within subpopulations are compared with the TWRs within the general population. One must decide whether the differences are real or caused by random fluctuations within the small isolates.