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  2. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. [1] It involves the analysis of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between them. [1] Bivariate analysis can be helpful in testing simple hypotheses of association.

  3. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    The multivariate probit model is a standard method of estimating a joint relationship between several binary dependent variables and some independent variables. For categorical variables with more than two values there is the multinomial logit. For ordinal variables with more than two values, there are the ordered logit and ordered probit models.

  4. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    A study by Kock suggests that the probability that Simpson's paradox would occur at random in path models (i.e., models generated by path analysis) with two predictors and one criterion variable is approximately 12.8 percent; slightly higher than 1 occurrence per 8 path models. [25]

  5. Interaction (statistics) - Wikipedia

    en.wikipedia.org/wiki/Interaction_(statistics)

    Interaction effect of education and ideology on concern about sea level rise. In statistics, an interaction may arise when considering the relationship among three or more variables, and describes a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two causes are not additive).

  6. Bivariate data - Wikipedia

    en.wikipedia.org/wiki/Bivariate_data

    In some instances of bivariate data, it is determined that one variable influences or determines the second variable, and the terms dependent and independent variables are used to distinguish between the two types of variables. In the above example, the length of a person's legs is the independent variable. The stride length is determined by ...

  7. This is the ideal age gap for a relationship that lasts - AOL

    www.aol.com/ideal-age-gap-relationship-lasts...

    Interestingly, that figure rose to 39 per cent for couples with a 10-year age gap and a shocking 95 per cent for those with a 20-year age gap. So, just how big is too big of an age difference?

  8. Why are age gap relationships controversial? - AOL

    www.aol.com/news/why-age-gap-relationships...

    All famous couples in age gap relationships with an age difference of at least 10 years. 47-year-old actor Leonardo DeCaprio is known for only dating women under the age of 25. "He is now dating a ...

  9. Rank correlation - Wikipedia

    en.wikipedia.org/wiki/Rank_correlation

    "One can derive a coefficient defined on X, the dichotomous variable, and Y, the ranking variable, which estimates Spearman's rho between X and Y in the same way that biserial r estimates Pearson's r between two normal variables” (p. 91). The rank-biserial correlation had been introduced nine years before by Edward Cureton (1956) as a measure ...