This methodological investigation aims to define a concept of asymmetry for qualitative variables, quantify it, and show its validity. A panel of five expert judges and Monte Carlo simulations were used. The statistic Mean Difference in Frequency (MDF) between pairs of categories ordered by frequency homogeneity was defined. The MDF statistic showed a behavior adjusted to expectations with different variants of the binomial distribution. The correlation between the mean skewness score of the judges and MDF was very high. To obtain interpretive guiding cutoffs, 20,000 samples of sizes 20, 40, 100, 200, 500, and 1000 were simulated, drawn from a binomial distribution. It is concluded that MDF is validity to measure asymmetry in qualitative variables.

Los objetivos del estudio fueron determinar las propiedades psicométricas de la Escala de Actitudes hacia la Estadística en México. En este estudio instrumental, se analizó una muestra no probabilística de 383 estudiantes de psicología mexicanos que respondieron a dos escalas actitudinales. El modelo bifactor definido por un factor general y tres factores específicos (seguridad, agrado-utilidad y motivación) mostró las mejores propiedades de ajuste a los datos y de validez convergente en sus modelos de medida. La actitud promedio fue neutra y más positiva en hombres que en mujeres. El factor general de actitud hacia la estadística tuvo correlación alta con actitud hacia la investigación. Se concluye el bifactor de tres factores representa mejor la relación entre los ítems que el modelo original de cinco factores correlacionados.

This methodological investigation aims to define a concept of asymmetry for qualitative variables, quantify it, and show its validity. A panel of five expert judges and Monte Carlo simulations were used. The statistic Mean Difference in Frequency (MDF) between pairs of categories ordered by frequency homogeneity was defined. The MDF statistic showed a behavior adjusted to expectations with different variants of the binomial distribution. The correlation between the mean skewness score of the judges and MDF was very high. To obtain interpretive guiding cutoffs, 20,000 samples of sizes 20, 40, 100, 200, 500, and 1000 were simulated, drawn from a binomial distribution. It is concluded that MDF is validity to measure asymmetry in qualitative variables.

The objective of this methodological study is to define and develop a qualitative peakedness measure and to test its validity. One hundred twenty qualitative distributions were generated from binomial distributions. The percentile kurtosis and the average of five judges when visually assessing the degree of peakedness were used as validity criteria. Peakedness was defined as the standout of the peak between the shoulders. From the frequencies of the nominal categories, it was specified how to chart a bar diagram and measure the distance from the peak to the shoulders. The statistic showed a behavior adjusted to expectations. Its correlation with average inter-judge peakedness was .87 and with percentile kurtosis −.38. It is concluded that a concept of qualitative peakedness can be defined and measured reliably.

The objectives of the study were to determine the psychometric properties of the Scale of Attitudes towards Statistics in Mexico. In this instrumental study, a non-probabilistic sample of 383 Mexican psychology students who responded to two attitude scales was analyzed. The bifactor model with three specific factors (safety, pleasure-usefulness, and motivation) showed the best properties of fit and convergent validity. The average attitude was neutral and more positive in men than in women. The general factor had a high correlation with attitude towards research. It is concluded that the three-factor bifactor model represents the relationship between the items better than the original five-factor model.

Qualitative variables are of great importance in the social sciences and descriptive measures of variability and shape have been developed for these variables, but they are little used. One of the main reasons is that they are not available in statistical software. This paper focuses on a recently introduced measure of variability, the Universal Variation Ratio, which enhances upon variation ratios previously formulated. This article aims to propose the calculation of its standard error and confidence interval and to provide a script for its computation using the R program. It applies to two scenarios: with one mode and with two or more modes. It is recommended to integrate this variability measure into data analysis procedures.

Qualitative variables are of great importance in the social sciences and descriptive measures of variability and shape have been developed for these variables, but they are little used. One of the main reasons is that they are not available in statistical software. This paper focuses on a recently introduced measure of variability, the Universal Variation Ratio, which enhances upon variation ratios previously formulated. This article aims to propose the calculation of its standard error and confidence interval and to provide a script for its computation using the R program. It applies to two scenarios: with one mode and with two or more modes. It is recommended to integrate this variability measure into data analysis procedures.

The objective of this methodological study is to define and develop a qualitative peakedness measure and to test its validity. One hundred twenty qualitative distributions were generated from binomial distributions. The percentile kurtosis and the average of five judges when visually assessing the degree of peakedness were used as validity criteria. Peakedness was defined as the standout of the peak between the shoulders. From the frequencies of the nominal categories, it was specified how to chart a bar diagram and measure the distance from the peak to the shoulders. The statistic showed a behavior adjusted to expectations. Its correlation with average inter-judge peakedness was .87 and with percentile kurtosis −.38. It is concluded that a concept of qualitative peakedness can be defined and measured reliably.

The objective of this methodological study is to define and develop a qualitative peakedness measure and to test its validity. One hundred twenty qualitative distributions were generated from binomial distributions. The percentile kurtosis and the average of five judges when visually assessing the degree of peakedness were used as validity criteria. Peakedness was defined as the standout of the peak between the shoulders. From the frequencies of the nominal categories, it was specified how to chart a bar diagram and measure the distance from the peak to the shoulders. The statistic showed a behavior adjusted to expectations. Its correlation with average inter-judge peakedness was .87 and with percentile kurtosis ?.38. It is concluded that a concept of qualitative peakedness can be defined and measured reliably.

Qualitative variables are of great importance in the social sciences and descriptive measures of variability and shape have been developed for these variables, but they are little used. One of the main reasons is that they are not available in statistical software. This paper focuses on a recently introduced measure of variability, the Universal Variation Ratio, which enhances upon variation ratios previously formulated. This article aims to propose the calculation of its standard error and confidence interval and to provide a script for its computation using the R program. It applies to two scenarios: with one mode and with two or more modes. It is recommended to integrate this variability measure into data analysis procedures.

The objectives of the study were to determine the psychometric properties of the Scale of Attitudes towards Statistics in Mexico. In this instrumental study, a non-probabilistic sample of 383 Mexican psychology students who responded to two attitude scales was analyzed. The bifactor model with three specific factors (safety, pleasure-usefulness, and motivation) showed the best properties of fit and convergent validity. The average attitude was neutral and more positive in men than in women. The general factor had a high correlation with attitude towards research. It is concluded that the three-factor bifactor model represents the relationship between the items better than the original five-factor model.

This methodological investigation aims to define a concept of asymmetry for qualitative variables, quantify it, and show its validity. A panel of five expert judges and Monte Carlo simulations were used. The statistic Mean Difference in Frequency (MDF) between pairs of categories ordered by frequency homogeneity was defined. The MDF statistic showed a behavior adjusted to expectations with different variants of the binomial distribution. The correlation between the mean skewness score of the judges and MDF was very high. To obtain interpretive guiding cutoffs, 20,000 samples of sizes 20, 40, 100, 200, 500, and 1000 were simulated, drawn from a binomial distribution. It is concluded that MDF is validity to measure asymmetry in qualitative variables.