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The basic statistics module is essential for a preliminary data analysis, as well as for a more detailed look at the data. Various tools from this module can also be used to test whether the data are consistent with assumptions needed for a successful application of other statistical methods. Some of the basic and common assumptions about data are: normality, independence and homogeneity. Therefore, no outliers and gross errors should occur in the data.

PDF Basic Statistics - Pdf manual

Protocol:
  • Classical parameters: Arithmetic mean, Lower limit, Upper limit, Variance, Standard deviation, Skewness, Difference from 0, Kurtosis, Difference from 3, Half-sum, Modus, t-test
  • Robust parameters: Median, CI lower, CI upper, Standard deviation, Variance, 10% trimmed mean, 20% trimmed mean, 40% trimmed mean
  • Runs test, Small sample analysis, Test for normality, Outliers detection, Homogeneity, Significance of autocorrelation, Sign test,
  • Test for linear trend, Slope, mean and median smoother, Smoothed values, Residuals
Plots:
Histogram, QQ-graph, Jittered dot diagram, Probability density function, Boxplot, Autocorrelation, Trends, Quantile plot, PP-plot, Quantiles box plot, Half sum plot, Symmetry plot, Kurtosis plot, Circle plot
 
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