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DEFINING STATISTICAL RELATIONSHIPS BETWEEN QUANTITATIVE AND DICHOTOMOUS VARIABLES: THE MOVING AVERAGE METHOD AND THE STUDENT'S T TEST |
A.N. Varaksin, Yu.V. Shalaumova, E.D. Konstantinova, T.A. Maslakova
A new method for assessing the statistical relationship between the quantitative variable Y and the dichotomous variable X, which takes two values: X=0 and X=1, is proposed. The technique is based on dividing the quantitative variable Y into strata using the moving average method and calculating the average values in strata for the variables Y and X. As a result of stratification, the dichotomous variable X turns into a quantitative variable. After such a transformation of the variable X, the statistical relationship between Y and X can be analyzed by linear regression methods and, in some cases, by methods of analysis of variance (when the new quantitative variable X can be considered as a rank variable). Thus, the proposed methodology expands the set of methods for analyzing statistical relationships between quantitative and dichotomous variables. The use of moving average methods also makes it possible to visualize the relationship between the studied variables, which is important for applied applications, for example, in medical and environmental research. A comparison of the new methodology with the two main existing methods for studying statistical relationships between quantitative and dichotomous variables is carried out: 1) Student’s test; 2) logistic regression. This article is devoted to the Student’s t test; analysis of logistic regression will be published in the next article. It is shown that, in some cases, the use of a moving average makes it possible to fi nd a statistically signifi cant relationship between Y and X where it is not detected by traditional methods of mathematical statistics.
Keywords: quantitative and dichotomous variables; Student’s t-test; moving average method; linear regression; analysis of variance; body mass index; smoking.
DOI: 10.25791/esip.03.2021.1213
Pp. 03-09. |
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