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Descriptive statistics (including Box plots and scattergrams)
Before using advanced analysis methods like, for example, discriminant analysis or multiple regression, you must first of all reveal the data in order to identify trends, locate anomalies or simply have available essential information such as the minimum, maximum or mean of a data sample. XLSTAT offers you a large number of descriptive statistics and charts which give you a useful and relevant preview...
Univariate plots
Before using advanced analysis methods you must first of all reveal the data in order to identify trends, locate anomalies or simply have available essential information such as the minimum, maximum or mean of a data sample. XLSTAT offers you a large number of descriptive statistics and charts which give you a useful and relevant preview of your data. Although you can select several variables (or...
DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
What is DBSCAN ? DBSCAN stands for Density-based Spatial Clustering of Applications with Noise proposed by Ester, Kriegel, Sander and Xu in 1996. It is the most widely used unsupervised learning method among density-based clustering methods. There are several advantages to using this type of method: the ability to create an unknown number of classes, to create classes with non-convex shapes and the...
Parallel coordinates plots
What is Parallel Coordinates Visualization This visualization method is useful for data analysis when you need to describe groups using variables. For example, this method could be used on groups generated by Agglomerative Hierarchical Clustering. Using this method you are able to visually determine which variables are discriminative. Structure of a Parallel Coordinates plot If you consider N observations...
Statistical Power for comparing correlations
Statistical Power of correlation comparison tests XLSTAT offers a test to compare correlations. XLSTAT can calculate the power or the number of observations necessary for this test. When testing a hypothesis using a statistical test, there are several decisions to take: The null hypothesis H0 and the alternative hypothesis Ha. The statistical test to use. The type I error also known as alpha. It occurs...
Friedman test
What is the Friedman non parametric test The Friedman test is a non-parametric alternative to the repeated measures ANOVA where the assumption of normality is not acceptable. It is used to test if k paired samples (k>2) of size n, come from the same population or from populations having identical properties as regards the position parameter. As the context is often that of the ANOVA with two factors,...
Normality tests
What are normality tests Assuming a sample is normally distributed is common in statistics. But checking that this is actually true is often neglected. For example, the normality of residuals obtained in linear regression is rarely tested, even though it governs the quality of the confidence intervals surrounding parameters and predictions. Normality tests are associated to the null hypothesis that...
GARCH
The Generalized Autoregressive Conditional Heteroscedastic model of order p,q, also known as GARCH (p,q), is a time series model that takes into account volatility, an important characteristic of financial data (e.g. volatility of asset returns). Forecasting volatility is useful in financial risk assessment. The GARCH function implemented in XLSTAT-R calls the garch function of the tseries library...
McNemar's test
McNemar's test definition and advantages McNemar’s test is a special case of the Cochran’s Q test when there are only two treatments. As for the Cochran’s Q test, the variable of interest is binary. However, the McNemar’s test has two advantages: Obtaining an exact p-value is possible; The data can be summarized in a 2x2 contingency table. In the case of the two-tailed (or two-sided) test, the null...
Canonical Correspondence Analysis (CCA and partial CCA)
What is Canonical Correspondence Analysis Canonical Correspondence Analysis (CCA) has been developed to allow ecologists to relate the abundance of species to environmental variables with the assumption that relationships are gaussian. However, this method can be used in other domains. Geomarketing and demographic analyses should be able to take advantage of it. Canonical Correspondence Analysis allows...