children

<p>The data used here is a contingency table that summarizes the answers given
by different categories of people to the 
following question : according to you, 
what are the reasons that can make hesitate a woman or a couple to have 
children?</p>

datasets

Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).

Francois Husson

FactoMineR

Multivariate Exploratory Data Analysis and Data Mining

children function

<p>A data frame with 18 rows and 8 columns. Rows represent the different reasons mentioned,
columns represent the different categories (education, age) people belong to.</p>

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children: Children (data)

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