化学学习动机的调查分析

作者运用教育心理学的课堂成就动机理论结合化学教学实际 ,选取了 14种化学学习动机进行问卷调查 ,并进行总体统计分析和抽样统计分析 ,得出了这样的结论。化学教师可以在教学中有效地培养 ,激发和强化学生的化学学习动机 ,提高教与学的效率 ,更好地培养学生的创新精神和实践能力。     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.     

A strong law of large numbers for independent random variables under non-additive probabilities

Abstract

Under non‐additive probabilities, cluster points of the empirical average have been proved to quasi-surely fall into the interval constructed by either the lower and upper expectations or the lower and upper Choquet expectations. In this paper, based on the initiated notion of independence, we obtain a different Marcinkiewicz-Zygmund type strong law of large numbers. Then the Kolmogorov type strong law of large numbers can be derived from it directly, stating that the closed interval between the lower and upper expectations is the smallest one that covers cluster points of the empirical average quasi-surely.     

An improved alternative estimation procedure for current population mean in presence of positively and negatively correlated auxiliary variables in two-occasion rotation patterns

Abstract

The present study confirms the influential role of a positively and a negatively correlated auxiliary variables in enhancing the precision of estimates of current population mean in two occasion rotation (successive) sampling. Exponential-type estimators of current population mean have been proposed for three different situations: (i) the information on a positively correlated auxiliary variable is readily available on both occasions (ii) the information on a negatively correlated auxiliary variable is readily available on both occasions and (iii) the information on both positively and negatively correlated auxiliary variables are readily available on both the occasions. The characteristics of the proposed estimators have been explored and their efficacious performances are compared with the natural and recent contemporary estimators. Optimum replacement strategies of the proposed estimation procedures have been formulated. Simulation and empirical studies are carried out to justify the proposition of the proposed estimators and appropriate recommendations have been put forward to the survey practitioners.     

中国货币政策的利率规则——基于金融状况指数的分析

为检验中国中央银行是否已将金融市场状况纳入货币政策的框架,采用HTVPVAR模型的脉冲响应构建中国金融市场状况指数,检验结果显示:以金融市场状况指数为转换变量的STR模型形式的利率规则能较好地拟合实际数据,政策利率对通货膨胀缺口的变动存在非线性调整,且金融市场的景气（不景气）将增强（减弱）货币政策对通货膨胀缺口的反应程度。     

Throughput and delay analysis of an opportunistic tree algorithm

Tree algorithms are a well-known class of random access algorithms with a provable maximum stable throughput under the infinite population model (as opposed to ALOHA or the binary exponential backoff algorithm). In this article, we propose a tree algorithm for opportunistic spectrum usage in cognitive radio networks. A channel in such a network is shared among so-called primary and secondary users, where the secondary users are allowed to use the channel only if there is no primary user activity. The tree algorithm designed in this article can be used by the secondary users to share the channel capacity left by the primary users.

We analyze the maximum stable throughput and mean packet delay of the secondary users by developing a tree structured Quasi-Birth Death Markov chain under the assumption that the primary user activity can be modeled by means of a finite state Markov chain and that packets lengths follow a discrete phase-type distribution.

Numerical experiments provide insight on the effect of various system parameters and indicate that the proposed algorithm is able to make good use of the bandwidth left by the primary users.     

A combinatorial study of two-periodic random walks

Two-periodic random walks have up-steps and down-steps of one unit as usual, but the probability of an up-step is α after an even number of steps and β = 1 ? α after an odd number of steps, and reversed for down-steps. This concept was studied by Böhm and Hornik^{[2 Böhm, W.; Hornik, K. On two-periodic random walks with boundaries. Stoch. Models 2010, 26, 165–194.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]]}. We complement this analysis by using methods from (analytic) combinatorics. By using two steps at once, we can reduce the analysis to the study of Motzkin paths, with up-steps, down-steps, and level-steps. Using a proper substitution, we get the generating functions of interest in an explicit and neat form. The parameters that are discussed here are the (one-sided) maximum (already studied by Böhm and Hornik^{[2 Böhm, W.; Hornik, K. On two-periodic random walks with boundaries. Stoch. Models 2010, 26, 165–194.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]]}) and the two-sided maximum. For the asymptotic evaluation of the average value of the two-sided maximum after n random steps, more sophisticated methods from complex analysis (Mellin transform, singularity analysis) are required. The approach to transfer the analysis to Motzkin paths is, of course, not restricted to the two parameters under consideration.