The correct answer is False. Andrews curves are a method for visualizing multivariate data that is based on the idea of projecting the data onto a sequence of low-dimensional subspaces. This allows the data to be visualized in a way that is both compact and informative. However, Andrews curves do not allow one to plot the data in its original, high-dimensional form.
Andrews curves are a type of smooth curve that can be used to represent a set of data points. The curves are constructed by iteratively projecting the data onto a sequence of lower-dimensional subspaces. The first projection is onto the line spanned by the first two data points. The second projection is onto the plane spanned by the first three data points, and so on. The curves are then constructed by connecting the projected data points.
Andrews curves can be used to visualize multivariate data in a way that is both compact and informative. The curves can be used to identify clusters in the data, to visualize the relationships between different variables, and to assess the dimensionality of the data.
However, Andrews curves do not allow one to plot the data in its original, high-dimensional form. This is because the curves are constructed by projecting the data onto a sequence of lower-dimensional subspaces. As a result, some of the information in the original data is lost.
In conclusion, the correct answer to the question “Andrews curves allow one to plot multivariate data” is False. Andrews curves are a method for visualizing multivariate data that is based on the idea of projecting the data onto a sequence of low-dimensional subspaces. This allows the data to be visualized in a way that is both compact and informative. However, Andrews curves do not allow one to plot the data in its original, high-dimensional form.