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The objective of the study was to correlate the Reynolds Rias Intelligence Scale (RIAS) and the McCarthy Scale of Skills and Psychomotor Skills for Children (MSCA), for the evaluation of cognitive development in children between 4 and 6 years of age, by means of a cross-sectional correlational study, with a sample of 70 children. The results obtained through a simple regression model confirm that there is a statistically significant correlation between the RIAS and MSCA variables, with a correlation coefficient of .865 and an adjusted R-squared of 98.5%, which indicates the high level of explanation of the model, also fulfilling all the residual tests to corroborate the quality of the prognostic model. Evidencing the significant validity of using the RIAS Scale in the evaluation of cognitive development in children from 4 to 6 years old. [ABSTRACT FROM AUTHOR]

This article basically consists of defining what it is, mentioning and explaining the applications of correlation and self-correlation. Using the tools provided by Matlab, it's intend to apply all these correlation concepts to a signal that could be random, and make an algorithm that evaluates the behavior of the chosen signal. It is intended to give information about applications in different areas of science, engineering, statistics and medicine. [ABSTRACT FROM AUTHOR]

This paper presents a comparative study of calculating the reorder point when the daily demand for goods is correlated with lead time and both variables have a Poisson probability distribution and when variables are uncorrelated. For the illustrative case, there has been difference of reorder point calculated with both methods, which is due to correlation between the variables is significant. If correlation coefficient takes negative or positive high values, then the differences in calculated reorder point with the two methods are significant. These differences also depend on the service level managed. If the correlation coefficient is positive, the traditional methodology underestimates the reorder point and it overestimates if the correlation is negative. Therefore it is recommended that before estimating the reorder point, to calculate the correlation coefficient between the two variables and apply the Wang equations if the coefficient falls between -0.4 and -1 or between 0.4 and 1. The minimum inventory cost was obtained with a correlation coefficient of 0.4, which depends on the cost structure of stockouts and maintenance. If the stockout cost is high compared to the maintenance, the minimum cost is obtained with a higher value of the correlation coefficient. [ABSTRACT FROM AUTHOR]