This is a Data Science Problem. There could be only one or more than one answer for all the problems. Select all that applies.

There could be only one or more than one answer for all the problems. Select all that applies.

Q2 PCA 2 Points Q2.1 Components 1 Point The singular value for the first principal component is always (select all that apply): Greater than or equal to zero Greater than one Larger than the other singular values At least as large as the other singular values None of these Submit Q2.2 Scree plots 1 Point Given that that PCA was applied to some data set, which of the following statement(s) describe the use of a scree plot? Compare the amount of total variance accounted for by each principal component. Identify clusters in the data. Assess whether a 2-d scatter plot is an appropriate visualization of the data. Visualize the data using a lower-dimensional projection. Identify the most informative variables in the data Submit Q3 Centering 1 Point For which of the following reason(s) are the variables (i.e. the columns) of a data set centered and scaled prior to using PCA? Singular value decomposition only applies to centered matrices Centering and scaling removes outliers from the data The singular values only express the total variance of the data after centering and scaling Submit Q2 PCA 2 Points Q2.1 Components 1 Point The singular value for the first principal component is always (select all that apply): Greater than or equal to zero Greater than one Larger than the other singular values At least as large as the other singular values None of these Submit Q2.2 Scree plots 1 Point Given that that PCA was applied to some data set, which of the following statement(s) describe the use of a scree plot? Compare the amount of total variance accounted for by each principal component. Identify clusters in the data. Assess whether a 2-d scatter plot is an appropriate visualization of the data. Visualize the data using a lower-dimensional projection. Identify the most informative variables in the data Submit Q3 Centering 1 Point For which of the following reason(s) are the variables (i.e. the columns) of a data set centered and scaled prior to using PCA? Singular value decomposition only applies to centered matrices Centering and scaling removes outliers from the data The singular values only express the total variance of the data after centering and scaling Submit