In general, college students have concerns about mastering the Statistics course. Several scientific articles suggest that methodologies in which the student is an active part of the educational process lead to their greater involvement in teaching activities and better results in their overall assessment. A modified form of the Mathematics course inspires this study. The Mathematics course precedes the Statistics course. This study presents students’ results from both affected courses for the last 12 years. The authors obtained the data from the Modular Academic Information System (MAIS). The study describes the Statistics course, which is a combination of the traditional form of teaching and learning with elements of active learning. The product is a redesign of this course. The proposed changes are based on the requirements of some stakeholders. The results are from a survey of course graduates, from the experience of online teaching during the COVID-19 pandemic, and the introduction of active-learning elements. The authors of the article point out the risks and opportunities they found in teaching the Statistics course.

Purpose: Economic optimum of quality is to find a balance beetween quality and costs of quality, therefore it is very important to monitor quality costs and economical indicators for valuation of cost effectiveness. All economic indicators can provide information to the company in terms of quality costs trend. All indicators are important for to improve TQM performance and for continual improvement of quality. The relative importance of economic indicators brings knowledges for managers to value cost effectiveness. Methodology/Approach:In this paper we use economical and statistical indicators for quality costs. We use in this paper model PAF, that it include prevention costs, evaluation costs, internal errors costs, external errors costs. We used these statistical indicators: Total costs, Individual simple cost index, cost ratio and cost structure.Findings: All these economic indicators can provide information to the company in terms of quality costs trend and their constant monitoring and management. Quality costs in relation to the profit participate with low percentage ie. the costs relative to quality significantly affect the generation of profits as their share of unit sales is too low, which is the most positive indicator of profit. While an index of costs in the monitored period decreases, which is in terms of this indicator positive phenomenon and it is not necessary to optimize the costs of the quality in relation to the reported sales.Originality/Value of paper: Cost effectiveness helps to improve TQM performance. TQM is a major business strategy for the company. Cost of quality influence to profit in the industrial company and profit is very important indicator for next business activities.

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Technical and technological developments in recent decades have stimulated the rapid development of methods and tools in the field of statistical process quality control, which also includes control charts. The principle of control charts defined by Dr. W. Shewhart has been known for more than 100 years. Since then, they have been used in many industries to monitor and control processes. This paper aims to assess the possibilities of use and the selection of the most suitable type of control chart for monitoring the quality of a process depending on its nature. This tool should help operators in monitoring coking time, which is one of the important control variables affecting the quality of coke production. The autoregressive nature of the variable being monitored was considered when selecting a suitable control chart from the group of options considered. In addition to the three traditional types of control charts (Shewhart’s, CUSUM, and EWMA), which were applied to the residuals of individual values of different types of ARIMA models, various statistical tests, and plots, a dynamic EWMA control chart was also used. Its advantage over traditional control charts applied to residuals is that it works with directly measured coking time data. This chart is intended to serve as a method to monitor the process. Its role is only to alert the process operator to the occurrence of problems with the length of the coking time.