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Research background: Recent research conducted in the field of entrepreneurship focuses on a better understanding of specific features of family businesses, which, according to estimates, make up 55–90 % of all business entities in EU member states. Foreign studies emphasise the greater resilience of family businesses in the face of adverse changes in their business environment, their ability of long-term survival and a higher degree of socially responsible behaviour. Purpose of the article: The main objective of this article is to find out whether there are statistically significant differences in performance between family and non-family businesses. The results will be used to determine whether the performance of family businesses differs from that of non-family businesses and to identify the specific features of family business. This information will also be used to enhance our knowledge of family entrepreneurship and to determine whether the conclusions of foreign studies are also valid for family businesses in the Czech Republic. Methods: We compared the results of two sets of data with financial results to identify differences in the performance of family and non-family businesses. Due to the fact that there is currently no register of family businesses, we first had to identify which are family businesses and complement them with non-family businesses. We used the accounting data of almost 8,000 businesses from the years 2014–2018 for this analysis. We defined 44 indicators and tested them using Welch’s t-test. Findings & value added: The analysed sample consists predominantly of small businesses. We identified a total of 30 ratios whose values differ statistically at a significance level of 5 %, for example current assets to sales, retained earnings to total assets and labour cost to sales. We can deduce from the results that there are differences in performance between family and non-family businesses.

Research background: Recent research conducted in the field of entrepreneurship focuses on a better understanding of specific features of family businesses, which, according to estimates, make up 55–90 % of all business entities in EU member states. Foreign studies emphasise the greater resilience of family businesses in the face of adverse changes in their business environment, their ability of long-term survival and a higher degree of socially responsible behaviour. Purpose of the article: The main objective of this article is to find out whether there are statistically significant differences in performance between family and non-family businesses. The results will be used to determine whether the performance of family businesses differs from that of non-family businesses and to identify the specific features of family business. This information will also be used to enhance our knowledge of family entrepreneurship and to determine whether the conclusions of foreign studies are also valid for family businesses in the Czech Republic. Methods: We compared the results of two sets of data with financial results to identify differences in the performance of family and non-family businesses. Due to the fact that there is currently no register of family businesses, we first had to identify which are family businesses and complement them with non-family businesses. We used the accounting data of almost 8,000 businesses from the years 2014–2018 for this analysis. We defined 44 indicators and tested them using Welch’s t-test. Findings & value added: The analysed sample consists predominantly of small businesses. We identified a total of 30 ratios whose values differ statistically at a significance level of 5 %, for example current assets to sales, retained earnings to total assets and labour cost to sales. We can deduce from the results that there are differences in performance between family and non-family businesses.

Research background: Recent research conducted in the field of entrepreneurship focuses on a better understanding of specific features of family businesses, which, according to estimates, make up 55–90 % of all business entities in EU member states. Foreign studies emphasise the greater resilience of family businesses in the face of adverse changes in their business environment, their ability of long-term survival and a higher degree of socially responsible behaviour. Purpose of the article: The main objective of this article is to find out whether there are statistically significant differences in performance between family and non-family businesses. The results will be used to determine whether the performance of family businesses differs from that of non-family businesses and to identify the specific features of family business. This information will also be used to enhance our knowledge of family entrepreneurship and to determine whether the conclusions of foreign studies are also valid for family businesses in the Czech Republic. Methods: We compared the results of two sets of data with financial results to identify differences in the performance of family and non-family businesses. Due to the fact that there is currently no register of family businesses, we first had to identify which are family businesses and complement them with non-family businesses. We used the accounting data of almost 8,000 businesses from the years 2014–2018 for this analysis. We defined 44 indicators and tested them using Welch’s t-test. Findings & value added: The analysed sample consists predominantly of small businesses. We identified a total of 30 ratios whose values differ statistically at a significance level of 5 %, for example current assets to sales, retained earnings to total assets and labour cost to sales. We can deduce from the results that there are differences in performance between family and non-family businesses.

Research background: Recent research conducted in the field of entrepreneurship focuses on a better understanding of specific features of family businesses, which, according to estimates, make up 55–90 % of all business entities in EU member states. Foreign studies emphasise the greater resilience of family businesses in the face of adverse changes in their business environment, their ability of long-term survival and a higher degree of socially responsible behaviour. Purpose of the article: The main objective of this article is to find out whether there are statistically significant differences in performance between family and non-family businesses. The results will be used to determine whether the performance of family businesses differs from that of non-family businesses and to identify the specific features of family business. This information will also be used to enhance our knowledge of family entrepreneurship and to determine whether the conclusions of foreign studies are also valid for family businesses in the Czech Republic. Methods: We compared the results of two sets of data with financial results to identify differences in the performance of family and non-family businesses. Due to the fact that there is currently no register of family businesses, we first had to identify which are family businesses and complement them with non-family businesses. We used the accounting data of almost 8,000 businesses from the years 2014–2018 for this analysis. We defined 44 indicators and tested them using Welch’s t-test. Findings & value added: The analysed sample consists predominantly of small businesses. We identified a total of 30 ratios whose values differ statistically at a significance level of 5 %, for example current assets to sales, retained earnings to total assets and labour cost to sales. We can deduce from the results that there are differences in performance between family and non-family businesses.

This study investigates how outliers of different magnitude impact the robustness of the twosample t-test. A simulation study approach is used to analyze the behavior of type I error rates when outliers are added to generated data. Outliers may distort parameter estimates such as the mean and variance and cause misleading test results. Previous research has shown that Welch’s ttest performs better than the traditional Student’s t-test when group variances are unequal. Therefore these two alternative statistics are compared in terms of type I error rates when outliers are added to the samples. The results show that control of type I error rates can be maintained in the presence of a single outlier. Depending on the magnitude of the outlier and the sample size, there are scenarios where the t-test is robust. However, the sensitivity of the t-test is illustrated by deteriorating type I error rates when more than one outlier are included. The comparison between Welch’s t-test and Student’s t-test shows that the former is marginally more robust against outlier influence.

This study investigates how outliers of different magnitude impact the robustness of the twosample t-test. A simulation study approach is used to analyze the behavior of type I error rates when outliers are added to generated data. Outliers may distort parameter estimates such as the mean and variance and cause misleading test results. Previous research has shown that Welch’s ttest performs better than the traditional Student’s t-test when group variances are unequal. Therefore these two alternative statistics are compared in terms of type I error rates when outliers are added to the samples. The results show that control of type I error rates can be maintained in the presence of a single outlier. Depending on the magnitude of the outlier and the sample size, there are scenarios where the t-test is robust. However, the sensitivity of the t-test is illustrated by deteriorating type I error rates when more than one outlier are included. The comparison between Welch’s t-test and Student’s t-test shows that the former is marginally more robust against outlier influence.

When comparing two independent groups, psychology researchers commonly use Student's t-Tests. Assumptions of normality and homogeneity of variance underlie this test. More often than not, when these conditions are not met, Student's t-Test can be severely biased and lead to invalid statistical inferences. Moreover, we argue that the assumption of equal variances will seldom hold in psychological research, and choosing between Student's t-Test and Welch's t-Test based on the outcomes of a test of the equality of variances often fails to provide an appropriate answer. We show that the Welch's t-Test provides a better control of Type 1 error rates when the assumption of homogeneity of variance is not met, and it loses little robustness compared to Student's t-Test when the assumptions are met. We argue that Welch's t-Test should be used as a default strategy.

When comparing two independent groups, psychology researchers commonly use Student's t-Tests. Assumptions of normality and homogeneity of variance underlie this test. More often than not, when these conditions are not met, Student's t-Test can be severely biased and lead to invalid statistical inferences. Moreover, we argue that the assumption of equal variances will seldom hold in psychological research, and choosing between Student's t-Test and Welch's t-Test based on the outcomes of a test of the equality of variances often fails to provide an appropriate answer. We show that the Welch's t-Test provides a better control of Type 1 error rates when the assumption of homogeneity of variance is not met, and it loses little robustness compared to Student's t-Test when the assumptions are met. We argue that Welch's t-Test should be used as a default strategy.

When comparing two independent groups, psychology researchers commonly use Student's t-Tests. Assumptions of normality and homogeneity of variance underlie this test. More often than not, when these conditions are not met, Student's t-Test can be severely biased and lead to invalid statistical inferences. Moreover, we argue that the assumption of equal variances will seldom hold in psychological research, and choosing between Student's t-Test and Welch's t-Test based on the outcomes of a test of the equality of variances often fails to provide an appropriate answer. We show that the Welch's t-Test provides a better control of Type 1 error rates when the assumption of homogeneity of variance is not met, and it loses little robustness compared to Student's t-Test when the assumptions are met. We argue that Welch's t-Test should be used as a default strategy., SCOPUS: ar.j, info:eu-repo/semantics/published

This paper provides a model-based method for analysis and hypothesis testing for paired data where one source of data has to be validated against another source of data that contains subjective and dynamic errors. This study deals with human-observed flow counts collected from traffic videos of freeway cameras. The available videos are mainly used for the purpose of manual observation by transportation personnel in case of emergency. This amounts to a varying inconsistency of the quality of the videos, which presents an additional challenge when analyzing the data. Video processing cannot be performed due to the mentioned issues with regard to the video quality. The processing has to be manually performed by humans who unfortunately have an inherent bias. If the video data have to be used for validating flow detector sensors, then a technique that performs validation with subjective and dynamic erroneous data as a result of the human bias is needed. This paper presents a methodology to deal with this issue. It is based on statistical testing with heteroscedasticity, which is demonstrated through a case study using data from traffic flow detectors and traffic cameras installed on highways in the Southern Nevada Region. A model for the relationship between the video ratings and the distribution of the human errors is developed taking into consideration the human bias. A method for identification of faulty detectors is also demonstrated based on the developed technique.