Statistical Analysis Methods Research Articles

The Influence of Entrepreneurship Knowledge, Personality, Family Environment on Entrepreneurial Interest of Undergraduate Students Class of 2021, Faculty of Economics and Business, University of Riau

This research aims to determine 1) the influence of entrepreneurial knowledge on students' interest in entrepreneurship, 2) the influence of personality on students' interest in entrepreneurship, 3) the influence of the environment on students' interest in entrepreneurship and 4) the influence of personality, entrepreneurial knowledge and the environment on students' interest in entrepreneurship. This research is quantitative with a multiple linear regression analysis model. This research uses data obtained from distributing questionnaires to 90 respondents. The sampling method used was the simple random sampling method. This research uses statistical data analysis methods using SPSS version 25. The results of the research show that 1) Knowledge of entrepreneurship has a positive and significant effect on students' interest in entrepreneurship, 2) Personality has a positive and significant effect on students' interest in entrepreneurship, 3) Family environment has a positive and significant effect on students' interest in entrepreneurship, 4) Knowledge of entrepreneurship, personality, and The family environment together has a positive and significant effect on interest in entrepreneurship. This means that the influence of these factors interacts with each other, where individuals who have good knowledge about entrepreneurship, a strong personality, and a positive family environment will have a great interest in pursuing an entrepreneurial career.

Application of Big Data Statistical Analysis Methods in the Field of Economic Management

Application of Big Data Statistical Analysis Methods in the Field of Economic Management

Analysis and discrimination of adhesive species using ATR-FTIR combined with Raman, and HS-GC-IMS together with multivariate statistical analysis

Identifying the species and origin of adhesives in criminal investigations aids in narrowing inquiry scope and supporting case detection. This study introduces two advanced combined analytical techniques for distinguishing adhesive species, including attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with Raman spectroscopy, and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) together with multivariate statistical analysis. ATR-FTIR categorized seven adhesives into three groups based on the base materials, with further differentiation achieved via Raman spectra. Analysis of volatile components identified 79 volatile organic compounds (VOCs), with esters being the most concentrated. The fingerprint profile clearly illustrated the characteristic fingerprint sequence and unique marker compounds of each adhesive, effectively enabling their differentiation. Multivariate statistical analysis methods, including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), heatmap, and hierarchical cluster analysis (HCA), were utilized to visually interpret the classification of adhesives. This integrated analytical approach provides a comprehensive analysis of adhesive compositions, facilitating the diversification and precision of adhesive species identification, and broadening the scope for detecting and analyzing trace evidence in forensic science.

Stakeholders’ Opinion on Geotourism Characteristics of Hummanaya Destination, Sri Lanka

Geotourism is a niche market that contributes to sustaining and even enhancing the geographical characteristics of a territory, including the abiotic, biotic, and cultural (ABC) attributes of destinations. It uplifts the living standards of local communities and provides opportunities for visitors to understand and appreciate the natural environment and the existing culture of the geosites. The aim of this research was to evaluate the geotourism characteristics of the Hummanaya tourism destination based on stakeholders’ opinions and to investigate the extent to which stakeholders are committed to adhering to geotourism principles. Primary and secondary data sources were utilized to collect the necessary data for this study. For gathering primary data, key informant interviews and participatory observations were conducted in the field using a semi-structured questionnaire, with purposive sampling employed. Unpublished documents served as secondary data. Descriptive statistical analysis and narrative interpretation methods were used to analyze the collected data. The study was able to identify the extent to which geotourism stakeholders adhere to geotourism principles. Specifically, regarding the principles of integrity, community involvement, community benefits, and tourist satisfaction, the informants provided positive responses. The findings reveal that the destination is perceived by tourists as a fascinating and unique tourist attraction in Sri Lanka. Most tourists reported being very satisfied or satisfied with the tourist attractions, facilities, and services provided by local facilitators, indicating that the destination meets tourists’ expectations. However, a significant issue is whether other stakeholders are satisfied with geotourism's contributions to protecting the destination's ABC attributes and improving the socio-economic status of local communities. Negative responses were noted concerning principles such as evolution, market selectivity, interactive interpretation, and market diversity. Therefore, necessary measures must be taken to conserve and develop the destination as a geosite and geotourism site.

Quantifying Agricultural Residues Biomass Resources and the Energy Potentials with Characterization of Their Nature and Ethiopian Case Consumption Inference

As the Ethiopian energy demand urges for fuel options, it is essential to identify biomass fuels and estimate their energy potential. This study quantified the agricultural residues’ biomass resources and their energy potential. Further analyzed and characterized the potential nature through quantitative and qualitative methodologies with descriptive, comparative, explanatory, and exploratory studies. Five-year crop yield data of 27 crops were collected from the Central Statistical Agency of Ethiopia. Conversion factors into energy were surveyed from the literature. Subsequently, the residues available and their energy potentials were estimated. Mathematical and statistical analysis methods were considered in an Excel sheet. A new measure of natural potential capacity for energy was defined in two views (resource and application). Accordingly, their potential capacities were rated and prioritized comparatively. The gross energy potential of all the residues was estimated to be 494.7 PJ. With 30% collecting efficiency, it corresponds to the imported petroleum fuel in 2018. Five major crops contributed to 80% of this gross potential. Maize and sorghum presented the highest potential due to their superior yields and good natural potential capacities. They are also well distributed in all the regions. Cotton and maize’s natural potential capacities are the best in both views. Generally, commercial crops presented better capacities than the major cereal crops. However, major crops’ energy potentials dominated due to their yields. These resources need mobilization into modern and commercially accessible fuel forms that await intervention. Densified and carbonized forms of consumption in nearby industries and households are most viable for the Ethiopian case.

Testing the operation of protection devices against parallel arc breakdown and spark gaps in the event of a ground fault

Testing the operation of protection devices against parallel arc breakdown and spark gaps in the event of a ground faultTHE PURPOSE. Develop a laboratory rig for testing parallel arc fault and spark gap protection devices for tripping in the event of a ground fault. Conduct laboratory rig tests with subsequent development of requirements for the use of parallel arc fault and spark gap protection devices for tripping in the event of a ground fault.METHODS. Mathematical and statistical methods of analysis were used to achieve the stated objective. Laboratory tests of parallel arc fault and spark gap protection devices for different network parameters for correct tripping in the event of a ground fault.RESULTS. Laboratory tests of parallel arc fault and spark gap protection devices for correct tripping in the event of a ground fault were conducted with different network parameters. The oscilloscope recorded the shape of the voltage and current curve in the event of a ground fault and the tripping time of the devices. The tested devices demonstrated the ability to recognize and disconnect a ground fault. The tripping time of the devices varies, however, does not exceed the established requirements.CONCLUSION. A laboratory stand has been developed for testing parallel arc breakdown and spark gap protection devices for operation during a ground fault. This stand makes it possible to test devices for adequate operation during a ground fault with subsequent certification. The tests conducted demonstrate the need to develop mandatory requirements for the device to standardize their operating algorithm. Therefore, the use of this protection device can contribute to safer operation of low-voltage electrical networks by preventing emergency situations and reducing the risk of fires. This is an important technical aspect for improving the reliability and safety of power supply.

Association mapping analysis (AMA) for morpho-agronomic traits and leaf aromatic compounds using SSR markers in three types of Perilla crop collected from South Korea.

Perilla is a representative leafy vegetable in South Korea. As K-Food (Korean food) is in the spotlight around the world, there is also increasing interest in Western countries in Perilla crop, an annual plant belonging to the Lamiaceae family. To discover comprehensive information, including genetic and phylogenetic relationships among the 80 native Perilla accessions, using three types of data: simple sequence repeat (SSR) marker data, volatiles profile data, and morpho-agronomic data. This study conducted genotypic and phenotypic analyses on 80 Perilla accessions of three types (cultivated var. frutescens, weedy var. frutescens, weedy var. crispa) from South Korea. Five groups (G1-G5) of the 80 Perilla accessions of the three types were differentiated into two different clusters [genotype-based clustering (GTC) and phenotype-based clustering (PTC)] based on an aroma sensory phenotypic test. A total of 314 alleles were confirmed using 55 Perilla SSR primer sets, and genetic variation in the 80 Perilla accessions was evaluated. Among the three statistical analysis methods, principal coordinate analysis (PCoA) and GTC using data of the 55 Perilla SSR markers revealed perfectly consistent results, whereas PTC produced a total of six clusters. The 10 Perilla SSR markers associated with and significantly correlated with both biochemical and morphological characteristics were selected. These findings are expected to provide valuable information for developing global South Korean Perilla cultivars for further studies in Perilla crop breeding programs.

Comprehensive investigation on the flavor difference in five types of tea from JMD (Camellia sinensis 'Jinmudan').

Jinmudan (JMD) is a high-aroma variety widely cultivated in China. The current study primarily focuses on the key volatile metabolites in JMD black and oolong teas,and investigates the impact of processing technologies on the aroma quality of JMD tea. However, few studies have explored the suitabilityof JMD for producing a certain type of tea or the characteristic quality differences among various JMD teas using multivariate statistical analysis methods. The principal volatile metabolites contributing to the floral quality of JMD tea are linalool, geraniol, indole and phenethyl alcohol. In JMD black tea (BT), the key volatile metabolites include methyl salicylate, geraniol, (E)-β-ocimene and phenethyl alcohol. In JMD oolong tea (OT), the key volatile metabolites include indole, linalyl valerate and phenethyl alcohol. In JMD yellow tea (YT), the key volatile metabolites include methyl salicylate, geraniol and terpinolene. In JMD white tea (WT), the key volatile metabolites include methyl salicylate, geraniol and terpinolene. In JMD green tea (GT), the key volatile metabolites include (E)-β-ocimene, indole and geraniol. Comparative analysis and KEGG pathway enrichment analysis revealed that flavonoid biosynthesis is the primary metabolic pathway responsible for the taste differences among various tea types. GT exhibited higher levels of phloretin, dihydromyricetin and galangin. The contents of vitexin, tricetin in YT were relatively higher. The contents of aromadendrin and naringenin in BT were higher, while OT contained higher levels of kaempferol. Additionally, WT showed higher contents of 3-O-acetylpinobanksin and 3,5,7-pinobanksin. This study explained the reasons for the quality differences of different JMD tea and provided a reliable theoretical basis for the adaptability of JMD tea. © 2024 Society of Chemical Industry.

The Mediating Role of Organizational Culture in the Effect of Organizational Climate on Organizational Commitment and Research

The purpose of this study is to examine the effect of organizational climate on organizational commitment and the mediating role of organizational culture in this effect. Organizational climate is defined as the perceived atmosphere in an organization, while organizational commitment refers to the loyalty of employees to the organization. Organizational culture, on the other hand, is a collection of values, rituals, and symbols arising from the organization's historical background that guides the behavior of employees. The main hypothesis of this research is that a positive organizational climate will increase organizational commitment and that organizational culture plays a mediating role in this process. To test this hypothesis, a survey has been conducted with employees of a company operating in the construction sector in Çanakkale. The survey consists of scales that measure employee perceptions of organizational climate, organizational commitment, and organizational culture. The data collected from the surveys have been evaluated with statistical analysis methods. The results of the analyses indicate that organizational climate has a significant effect on organizational commitment, which is strengthened through organizational culture.

Determination and identification of polyphenols in wine using mass spectrometry techniques

Mass spectrometry is crucial for analysing physicochemical and sensory properties, including colour, astringency, taste, and flavour, predicting ageing characteristics, and addressing stability issues in wine. Polyphenols are key chemical constituents in wine that are associated with health benefits and improve circulatory conditions. Advances in mass spectrometry ionisation techniques such as matrix-assisted laser desorption and ionisation and direct analysis in real-time offer high sensitivity for identifying important polyphenolic constituents in wine. High-resolution mass spectrometry, in combination with liquid chromatography, accurately identify and quantify polyphenolic compounds, even at low concentrations, and provides the possibility for further retrospective analysis and non-targeted analysis using statistical methods of data analysis. Ambient mass spectrometry techniques such as paper spray and low-temperature plasma allow solventless analysis, determining the geographical origin, authentication, and quality control of wine samples. This review will explore the potential benefits of using mass spectrometry to identify various polyphenols and polymeric polyphenols in wine, as well as recent developments and applications. Additionally, we will discuss determining antioxidant activity and total polyphenol content in wine.

Factors Influencing Peri-Urban Land Development in Ethiopia: Evidences from Assosa City

Like other developing countries, Ethiopia has adopted its land administration system (LAS) based on socio-economic, environmental, and administrative circumstances to allocate and use the land. However, the two ineffective lines of urban and rural land tenure guidelines and legal frameworks play a surprising strategic role in access to land and peri-urban land development. Comprehensive land policies are prospects for today's peri-urban areas to become tomorrow's huge cities. This paper aims to investigate the factors influencing peri-urban land development in Assosa Town and indicate the design of effective LAS. A mixed research approach was employed, and data was collected from both primary and secondary sources. The sample respondents were selected using purposive sampling techniques and descriptive and inferential statistical data analysis methods were employed. The findings revealed that bifurcated and ineffective legal and institutional frameworks, limited public-private participation, and technical constraints adversely affect peri-urban land development. The dichotomized land use development has neglected urban fringe areas and contributed to the prevailing negative peri-urban land developments. Development resulted with limited access to serviced land and deprived of land development permit. <i>Following this, peri-urban landholders became a crucial contributor to the development of peri-urban land in a negative manner.</i> Almost all sampled households developed their land contrary to the legal frameworks and standards. The estimated results of the binary logit model indicate that several factors influence peri-urban land development, including sex, monthly household income, access to official land and land information, land disputes, the alternative land development tool, and institutional integration. It is recommended to have an all-in-one land policy and administration strategy to promote sustainable development in the study area and beyond.

Identification process of time-related bias in pharmacoepidemiologic research based on a scoping review

Objective: To summarize the characteristics of pharmacoepidemiologic research involving diabetes patients, which were published in recent years, in terms of study design and analysis, and develop an identification process for time-related biases in pharmacoepidemiologic research. Methods: PubMed, Embase, CNKI and Wanfang were used for a systematical literature retrieval of relevant study papers published between January 1,2012 and September 26, 2022. Literature screening and data extraction were performed independently by two reviewers. Based on the mechanisms of different time-related biases and the characteristics of included study papers in terms of study design and analysis methods, an identification process for all types of time-related biases was developed. Results: A total of 281 study papers were included, of which 58 (20.64%) specifically mentioned certain time-related biases considered in the study. Based on the scoping review results, key points to identify time-related biases were summarized, involving data source, study design, control selection, comparator drugs, matching the duration of diabetes, identification of the washout period, identification of the induction/latency period, identification of the initiation of follow-up, identification of time window, statistical analysis methods, sensitivity analysis, and other design and analytical elements, in the identification process for time-related biases in pharmacoepidemiologic research. Conclusions: Time-related biases are common in pharmacoepidemiologic research and might significantly impact the study results. Based on scoping review results, this study further developed an identification process for time-related biases in pharmacoepidemiologic research, which will help researchers identify and avoid time-related biases and improve the reliability of related evidence in pharmacoepidemiologic research.

Appraising the Role of Strategic Control in Financial Performance: The Mediating Effect of the Resource Allocation Process—The Case of the Ministry of Finance–North Lebanon

This paper aims to appraise the influence of strategic control tactics on financial performance. The goal is to examine the mediating effect of the resource allocation process on the relationship between financial performance and five strategic control tactics. A quantitative hypothetico-deductive methodology was used in this study. A basic random sample of the Ministry of Finance–North Lebanon’s workforce was used to conduct an electronic questionnaire. A total of 232 valid responses were collected. Two statistical analysis methods, an exploratory and a confirmatory factor analysis, were implemented. The sample adequacy was confirmed by a KMO value higher than 0.7 before instigating the principal component analysis (PCA). The latter kept more than 60% of the initial data while structuring the data. The findings of the KMO and Barlett tests supported the adoption of PCA. The correlation matrix confirmed a statistically significant relationship between resource allocation, financial success, and strategic control techniques. The structural equation model (SEM) validated the linear correlations and statistical significance between the variables. The hypotheses were examined. Results confirmed that the model satisfactorily fits the data. The RMSEA is below the 0.05 threshold. The incremental indices are higher than 0.9. Results confirmed that the resource allocation process mediates the relationship between preventive control, operational control, special alert control, implementation control, and financial performance.

SP2.4 - Appendicetomy in pregnancy: a retrospective analysis of 39 cases between 2012-2022

Abstract Background Acute appendicitis is the commonest surgical emergency in pregnant women. Physiological changes during pregnancy can obscure symptoms. Prompt diagnosis and surgical intervention is essential to minimise risks such as sepsis and preterm labour. Objective This study aims to evaluate how gestational age, type of imaging, surgeons' expertise, and antibiotics management affect the surgical outcomes in pregnant patients with acute appendicitis. Methods A retrospective analysis of 39 obstetric cases between 2012 and 2022 in the Royal infirmary of Edinburgh. Statistical methods for analysis including ANOVA were used to compare different surgical techniques, and correlation assessments to investigate links between gestational age and aspects of post-operative care. Results The study found that the surgical method significantly impacted post-operative recovery, with laparoscopic procedures leading to shorter hospital stays and decreased antibiotic use compared to open surgeries (p=0.001169 for hospitalisation length and p=0.01049 for antibiotic course, respectively). Surgeon grade did not significantly alter these outcomes. There was a moderate correlation between gestational age and both post-operative antibiotic duration (r = 0.3293) and length of hospital stay (r = 0.3640. The varied use of imaging techniques across different stages of pregnancy suggests there is no consensus of best practice. Conclusion The study identifies a need for consistent guidelines on treating pregnant women with appendicitis, particularly regarding antibiotic use. The results support the preferential use of minimally invasive surgery and value MRI as a non-invasive diagnostic tool, both contributing to a comprehensive, multidisciplinary approach required for these complex clinical scenarios.

THE ROLE OF NON-GOVERNMENTAL ORGANIZATIONS IN THE SOCIO-PROFESSIONAL ORIENTATION OF YOUNG PEOPLE AND ITS IMPACT ON THE ECONOMIC DEVELOPMENT OF THE COUNTRY

Purpose of the research. The aim of the study is to elucidate the role of non-governmental organizations in facilitating the social adaptation and professional orientation of the younger generation in the country as a process of providing human resources for the country's economy.Methodology. The research employed systemic, statistical, and comparative analysis methods to assess the role of non-governmental organizations in supporting the socio-professional orientation of young people in Kazakhstan. The authors conducted a literature review of scholarly works on the research topic, which allowed for the examination of similar trends and effective approaches of advanced countries to address this issue, as well as to identify key aspects contributing to the successful socio-professional orientation of young people in the country.Originality / value of the research. The originality and value of the study lie in examining and evaluating the role of non-governmental organizations in supporting the socio-professional orientation of youth in Kazakhstan, taking into account the changes in institutional frameworks in accordance with the new reality. This understanding underscores that effective youth support requires not only the development of corresponding programs and projects but also the alteration of institutional mechanisms in such a way that these programs are successfully implemented and bring maximum benefit to society.Findings. Key aspects related to youth's choice of professional path, crucial for Kazakhstani youth, have been identified. At this stage, young people encounter a range of issues. It has been revealed that the adaptation of institutional mechanisms contributes to the more effective functioning of non-governmental organizations and increases their influence on the socio-professional orientation of youth. Practical recommendations for enhancing interaction between governmental and non-governmental organizations to ensure the most effective support for the socio-professional orientation of youth in Kazakhstan have been formulated. The role of nongovernmental organizations in strengthening institutional capacity in ensuring more consistent, result-oriented support for youth has been justified.

Coyote and Badger Optimization (CBO): A natural inspired meta-heuristic algorithm based on cooperative hunting

Optimization techniques play a pivotal role in refining problem-solving methods across various domains. These methods have demonstrated their efficacy in addressing real-world complexities. Continuous efforts are made to create and enhance techniques in the realm of research. This paper introduces a novel technique that distinguishes itself through its clarity, logical mathematical structure, and robust mathematical equations, particularly in the second phase. This study presents the development of a new metaheuristic algorithm named Coyote and Badger Optimization (CBO). CBO draws inspiration from the cooperative behaviors observed in honey badgers and coyotes, with a specific focus on their intriguing communication process. Utilizing the inherent traits of these animals, the proposed CBO algorithm offers an intuitive and effective solution for addressing engineering optimization challenges by providing the best fitness values. To validate CBO's effectiveness in real-time applications, complex engineering problems called pressure vessel design, feature selection in medical system, and tension-compression spring design are used as case studies for testing the proposed CBO compared to other recent algorithms. Additionally, ten benchmark functions and also statistical analysis methods (mean, standard deviation, confidence intervals, t-test, and Wilcoxon test) are used. Experimental results demonstrate that the CBO algorithm surpasses eleven recent algorithms when subjected to common ten benchmark functions. Additionally, CBO outperforms other recent eleven algorithms according to three different case studies. According to the ten benchmark functions (F1 to F10), CBO provides the minimum fitness values which are closed to the exact (standard) values; 0, 0, 0.003, 0.0002, -1.0316, 3.0058, 0.398, 0.02, 0.00076, and 0.000725 respectively. Related to statistical analysis, CBO provides the best mean, standard deviation, confidence intervals, t-test, and Wilcoxon test values. According to case studies, CBO provided the minimum cost value for pressure vessel design, the maximum accuracy value for feature selection, and the minimum cost value for spring design. Hence, CBO superiors other recent algorithms.

Characterizing and tracing the heavy metals' spatial distribution in karst surface river affected by acid mine drainage

A series of pollution problems have been caused by the drainage of closed coal mines. This study focuses on the XZ River in Guizhou Province, employing a comprehensive approach involving hydrochemical analysis, mathematical statistics, and one-dimensional water quality modeling to investigate the spatial evolution and source apportionment of heavy metals in karst surface rivers affected by AMD. The average pH, EC, and Eh values of groundwater and surface water in the XZ river basin were 6.27, 331 <i>μ</i>s/cm, 230 mV and 3.86, 1671.57 <i>μ</i>s/cm, 412.71 mV, respectively, indicating severe pollution of surface water by AMD. The study reveals that groundwater in the XZ River Basin is predominantly of the HCO<sub>3</sub>-Ca-Mg type, shifting to HCO<sub>3</sub>-SO<sub>4</sub>-Ca-Mg type with the influx of acid mine wastewater. Utilizing statistical methods for source apportionment analysis indicated that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr most likely originate from tributaries. Further analysis through one-dimensional water quality simulation confirmed that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr are attributed to tributaries. This suggests that XZ River is affected by pollution from different coal mines, primarily from coal mine M4, followed by coal mine M1.

Нелинейные главные компоненты биохимического профиля молочного скота пяти пород

Abstract. The purpose of this study was to identify and explain patterns of biochemical parameters in dairy cows, taking into account the characteristics of their breed. Methods. A comparison was made of samples of animals of five breeds (Holstein, Tagil, Suksun, Sychevsk, Istoben) according to 17 biochemical parameters. The total number of animals studied was 407. To analyze the obtained results, statistical analysis methods were used, including the method of nonlinear principal component analysis using the CATPCA (Categorical PCA) algorithm. Scientific novelty. The chosen method made it possible to summarize a large number of biochemical indicators and identify processes in which the studied groups of cows differed to a greater or lesser extent. Results. Five principal components were identified and interpreted, explaining a total of 67.4 % of the total variance. Some observed patterns may indicate the development of pathological conditions in animals. Similar biochemical patterns were observed, on the one hand, in cows of the Tagil, Holstein and Suksun breeds, and on the other, in the Istoben and Sychev breeds. The animals of the Suksun breed were closest to the physiological norm. More pronounced changes associated with a negative energy balance were observed in Holstein cows.

Analisis Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran Terbuka di Kota Medan: Periode 2017-2022

This research aims to analyze the factors that influence the level of open unemployment in Medan City during the 2017-2022 period. Variables considered in the analysis include population, minimum wage, and human development index. By using statistical analysis methods, the research results show that these factors have a significant influence on the unemployment rate in Medan City. Apart from that, the determinant test, F test, and T test were also carried out to test the relationship between the variables studied. The findings from this research provide valuable information for policy makers in designing more effective economic development strategies in Medan City. The implications of this research can be used as a basis for formulating policies that can reduce unemployment levels and improve people's welfare in the region.

Convergence rates of Metropolis–Hastings algorithms

AbstractGiven a target probability density known up to a normalizing constant, the Metropolis–Hastings algorithm simulates realizations from a Markov chain which are eventual realizations from the target probability density. A key element for ensuring a reliable Metropolis–Hastings simulation experiment is understanding how quickly the simulation will generate a representative sample from target density. This corresponds to understanding the convergence properties of the Metropolis–Hastings Markov chain. State‐of‐the‐art methods for convergence analysis of Metropolis–Hastings algorithms are considered and reviewed. Practically important topics are discussed for an interdisciplinary audience. This includes convergence properties in high dimensions, proper tuning, initialization, and limitations of current convergence analyses.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Markov Chain Monte Carlo Statistical and Graphical Methods of Data Analysis > Monte Carlo Methods Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory