Question

Univariate vs bivariate outliers

A) Univariate outliers affect one variable, while bivariate outliers affect two
B) Bivariate outliers affect one variable, while univariate outliers affect two
C) Both terms refer to the same concept
D) Neither univariate nor bivariate outliers exist

Answer 1

A) Univariate outliers affect one variable, while bivariate outliers affect two

The right answer is A, as univariate outliers affect one variable and bivariate outliers affect two. Both types of outliers can have substantial effects on statistical analysis such as regression analysis, and identifying them requires careful use of statistical tools.

Step-by-step explanation:

Regarding univariate and bivariate outliers, the correct answer to the question is:

A) Univariate outliers affect one variable, while bivariate outliers affect two.

Univariate outliers are extreme values that appear to deviate markedly from other observations on a single variable. On the other hand, bivariate outliers are points that have unusual values on two variables at the same time, which can influence relationships between variables, such as in regression analysis or correlation studies. For example, in a scatter plot, a bivariate outlier would not fall within the general cloud of points.

Influential points, while related to outliers, are data points that can significantly affect the results of a regression analysis. They are typically located far from other points, and their presence or absence can change the slope of the regression line and the strength of the correlation. Identifying outliers and influential points often requires statistical tools and can impact how the data is interpreted and used.