Some commonly occuring statistical analysis tasks are implemented in Igor procedures. They include the 1D Statistics Report package, the ANOVA Power Panel, plotting and convenience functions.
The 1D Statistics Report package is designed to simplify the analysis of a single 1D wave. The package produces a formatted notebook containing the results of the operations WaveStats and StatsQuantiles followed by several graphs. The graphs include a lag plot, an autocorrelation plot, a histogram, a spectral plot, box plot and a normal-probability plot.
The ANOVA Power Panel lets you compute various quantities relating to a one-way ANOVA for fixed-effect model. You can use the panel for experiment design.
| Function Name | What it does |
| statsAutoCorrPlot() | plots the autocorrelation of a wave |
| statsBoxPlot() | creates a single box plot |
| statsPlotHistogram() | creates a simple histogram plot |
| statsPlotLag() | creates a lag plot |
| statsProbPlot() | creates a probability plot ala NIST |
| WM_PlotBiHistogram() | creates a bi-histogram plot |
A collection of convenience functions is listed below. These functions are available by including AllStatsProcedures.ipf.
| Function Name | What it does |
| WM_2MeanConfidenceIntervals() | computes the confidence limits for two populations means |
| WM_BernoulliCdf() | returns the Bernulli CDF |
| WM_CIforPooledMean() | computes the confidence intervals for pooled means |
| WM_CompareCorrelations() | compares two correlation coefficients |
| WM_EstimateMinDetectableDiff() | computes minimum detectable difference for single sample |
| WM_EstimateReqSampleSize() | estimate the required sample size given sample variance |
| WM_EstimateReqSampleSize2() | estimate the required sample size given sample variance and power |
| WM_EstimateSampleSizeForDif() | computes sample size required to detect a specified difference in means |
| WM_GetANOVA1Power() | computes power in fixed effects one way ANOVA |
| WM_GetGeometricAverage() | computes a geometric average |
| WM_GetHarmonicMean() | computes the harmonic average |
| WM_GetPooledMean() | computes the pooled mean for two distributions from populations with same means |
| WM_GetPooledVariance() | computes the pooled variance for two populations |
| WM_MCPointOnRegressionLines() | tests the difference between two points which lie on two lines |
| WM_MeanConfidenceInterval() | computes the confidence interval about the mean |
| WM_OneTailStudentA() | returns the one-tail result for StudentA |
| WM_OneTailStudentT() | returns the one-tail result for StudentT |
| WM_RankForTies() | ranks data and accounts for possible ties |
| WM_RankLetterGradesWithTies() | ranks letter grades |
| WM_RegressionInversePrediction() | computes an inverse prediction for linear regression |
| WM_VarianceConfidenceInterval() | computes confidence interval for population variance |
| WM_WilcoxonPairedRanks() | computes positive and negative ranks for Wilcoxon Paired Ranks test |
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