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IntroductionPrincipal Component AnalysisCorrespondence Analysis Multiple Correspondence Analysis ClusteringMultiple Factor AnalysisTo concludeForum
Q1) In principal component analysis, variables with a large mean have more importance in the analysis variables should always be standardized if they come in different units variables should never be standardized if they have the same units standardization gives the same importance to all variables
Q2) The individuals plot: two individuals quite far apart on the first axis have very different values for many variables individuals close the center of gravity of the cloud have average values for many variables two individuals superposed on the principal plane (1-2 axes) have the same values for all variables two individuals superposed on the principal plane (1-2 axes) have similar values for the variables that are well-projected onto this plane.
Q3) For the variables, the graph with the correlation circle allows us to visualize the correlation matrix between variables the graph with the correlation circle helps us to interpret the individuals plot the cos of the angle between the arrows representing variables on the projection plane is equal to the correlation coefficient between the variables the cos of the angle between the arrows representing variables in the global space is equal to the correlation coefficient between the variables
Q4) The first factor axis (the first dimension) is the one that best-separates the points of the individuals represents the variable that is most related to the set of variables (in the R2 sense) is the one that contains the most information
Q5.1) The correlation between V1 and V5 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
Q5.2) The correlation between V1 and V7 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
Q5.3) The correlation between V2 and V4 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
Q5.4) The correlation between V1 and V3 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
Q5.5) The correlation between V7 and V8 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
Q5.6) The correlation between V5 and V6 is close to -1 is close to -0.5 is close to 0 is close to 0.5 is close to 1 cannot be discovered by looking at the plot - it can vary between -1 and 1
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