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The main aim of the paper was to investigate factors influencing flight delays of a European airline. Besides the identification and analysis of those factors the paper offers possible suggestions on how to eliminate the delays. The research is based on data acquired over the period of time spanning from June to September in 2008 – 2014. Analysis of contingency tables, including Pearson’s chi‑squared test, has been used for data processing. The dependencies have been presented in graphical form by using correspondence maps. The proportion of delayed flights reaches approx. 50 % during nearly the entire monitored period only in September the proportion drops to 45 %. Flight delays are most frequently caused by delays of previous flights of the same plane. These previous delayed flights are the main culprit of long delays and the frequency of delay occurrence caused by this reason increases significantly during the day. Longer delays of flights appear also due to technical maintenance or aircraft defects. On the contrary other factors such as operational control and crew duty norms, air traffic control and airport limitations tend to cause rather shorter delays of flights with the air traffic control encountering more problems with coordination of flights in the early morning. The supply and service companies also manage to eliminate long delays.

Genome-wide association studies the evaluation of association between candidate gene and disease status is widely carried out using Cochran-Armitage trend test. However, only a small number of research papers have evaluated the distribution of p-values for the Cochran-Armitage trend test. In this paper, an enhanced version of Cochran-Armitage trend test based on bootstrap approach is introduced. The achieved results confirm that the distribution of p-values of the proposed approach fits better to the uniform distribution, and it is thus concluded that the proposed method, which needs less assumptions in comparison with the conventional method, can be successfully used to test the genetic association.

Intermittent motion mechanisms are widely used in semiautomatic and automatic machinery. Currently, the most common are mechanisms with a one-way coupling or mechanisms of variable structure. The intermittent movement in these mechanisms is provided by breaking the kinematic chain, so their use is undesirable in high-speed machines. The paper presents and analyzes kinematics of planetary transmission with elliptical gears, which performs intermittent motion of output link without interruption of kinematic chain. A kinematic model of the mechanism is constructed, and there are obtained equations for determining the velocity analogue of the output link of the planetary gear. An experimental verification of the adequacy of the developed mathematical model was carried out on the example of studying the position function of the mechanism. The measurement errors were estimated using statistical methods. Using the chi-squared test, the hypothesis of a normal distribution of measurement errors was verified, and confidence interval was determined.

This paper deals with statistical inference procedure of multivariate failure time data when the primary covariate can be measured only on a subset of the full cohort but the auxiliary information is available. To improve efficiency of statistical inference, we use quadratic inference function approach to incorporate the intra-cluster correlation and use kernel smoothing technique to further utilize the auxiliary information. The proposed method is shown to be more efficient than those ignoring the intra-cluster correlation and auxiliary information and is easy to implement. In addition, we develop a chi-squared test for hypothesis testing of hazard ratio parameters. We evaluate the finite-sample performance of the proposed procedure via extensive simulation studies. The proposed approach is illustrated by analysis of a real data set from the study of left ventricular dysfunction.

In this paper we investigate a semiparametric testing approach to answer if the parametric family allocated to the unknown density of a two-component mixture model with one known component is correct or not. Based on a semiparametric estimation of the Euclidean parameters of the model (free from the null assumption), our method compares pairwise the Fourier’s type coefficients of the model estimated directly from the data with the ones obtained by plugging the estimated parameters into the mixture model. These comparisons are incorporated into a sum of square type statistic which order is controlled by a penalization rule. We prove under mild conditions that our test statistic is asymptotically $\chi^{2}_{1}$-distributed and study its behavior, both numerically and theoretically, under different types of alternatives including contiguous nonparametric alternatives. We discuss the counterintuitive, from the practitioner point of view, lack of power of the maximum likelihood version of our test in a neighborhood of challenging non-identifiable situations. Several level and power studies are numerically conducted on models close to those considered in the literature, such as in McLachlan et al. [21], to validate the suitability of our approach. We also implement our testing procedure on the Carina galaxy real dataset which low luminosity mixes with the one of its companion Milky Way. Finally we discuss possible extensions of our work to a wider class of contamination models.

The sharp decline in exports and industrial production, rising unemployment and rapidly eroding consumer confidence had a severe negative impact on tourism consumption. This paper explores the factors that affected tourist's behaviour, hence their preferences and holiday destination choice on the background of the economic crisis. It is focused on a qualitative methodology approach that is based on a questionnaire and a quantitative research based on statistical data. The research was structured to build an understanding of how the economic crisis affected the tourists that “consume” tourism products and which have made changes in their destination choices.