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👉 Uncorrelated

uncumber

👉 Uncorrelated means that two variables are not related or linearly dependent. Two variables, A and B, are said to be uncorrelated if their covariance (the product of the variances) is zero. In other words, they have no positive correlation or negative correlation between them. For example, consider two variables X and Y that both represent observations from a population: X = 10, 20, 30, 40 Y = 8,

uncorrugated

👉 Uncorrelated refers to two variables having no relationship or correlation between them. This means that there is no direct linear relationship between the two variables, and therefore, their values cannot be predicted with any degree of certainty based on their differences. For example, if we have two variables X and Y, where X can take on any value from 0 to 1 and Y can take on any value from -1 to 1 (with a zero correlation), then the uncorrelated relationship between them

uncorrelative

👉 Uncorrelatedly refers to two variables or random variables being independent of each other. This means that if one variable is observed, there is no correlation between it and another variable that has not yet been observed. In other words, the relationship between the two variables is completely independent of each other, meaning that they do not have any impact on each other's values. For example, consider a coin toss experiment where both the outcome of the first toss (heads or tails) and the outcome of the

uncorrelatedly

👉 Uncorrelated refers to two sets of data that are not related in any way. Two sets of data are considered uncorrelated if they have no correlation between them, meaning there is no relationship or linear dependence between the values of the variables. For example, if you have two sets of data: x1 and y1, and x2 and y2, then x1 and y1 will be independent (unrelated) to x2 and y2 because they are not related in any

uncorrelated