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A i is the number of data type A at sample site i, B i is the number of data type B at sample site i, K is the number of sites sampled and || is the absolute value. This index is probably better known as the index of dissimilarity (D). [44] It is closely related to the Gini index. This index is biased as its expectation under a uniform ...
A chart can represent tabular numeric data, functions or some kinds of quality structure and provides different info. The term "chart" as a graphical representation of data has multiple meanings: A data chart is a type of diagram or graph, that organizes and represents a set of numerical or qualitative data.
Multiple factor analysis (MFA) is a factorial method [1] devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups.
In the example above, the table might have categorical column labels representing the name (a qualitative variable) and age (a quantitative variable), with each row of data representing one person (the sampled experimental unit or category subdivision).
A graph or chart or diagram is a diagrammatical illustration of a set of data. If the graph is uploaded as an image file, it can be placed within articles just like any other image. Graphs must be accurate and convey information efficiently. They should be viewable at different computer screen resolutions.
MAXQDA Analytics Pro is the most advanced version of MAXQDA. Besides the MAXDictio module, it also integrates a comprehensive module for statistical analysis of qualitative data. The "Stats" module offers tools to statistically analyze MAXQDA project data or import and work with external quantitative data sets in Excel or SPSS.
Data visualization uses information displays (graphics such as, tables and charts) to help communicate key messages contained in the data. [46] Tables are a valuable tool by enabling the ability of a user to query and focus on specific numbers; while charts (e.g., bar charts or line charts), may help explain the quantitative messages contained ...
The data include quantitative variables =, …, and qualitative variables =, …,.. is a quantitative variable. We note: . (,) the correlation coefficient between variables and ;; (,) the squared correlation ratio between variables and .; In the PCA of , we look for the function on (a function on assigns a value to each individual, it is the case for initial variables and principal components ...