compareGroups(DF, plots = TRUE, xyTopLeft = TRUE, ABalt = c('two.sided', 'less', 'greater'), Walt = c('two.sided', 'less', 'greater'), CEPtype = 'CorrNormal', CEPlevel = 0.5, CIlevel = 0.95, conversion = 'm2cm')Series (a factor), and either Point.X, Point.Y or X, Y defining the bullet holes. Variables Distance (distance to target), Aim.X, Aim.Y (point of aim) are useful - if they are missing, a warning is given and a default assumed.getCEP.getMOA.xyTopLeft=FALSE. If groups appear to be upside-down, xyTopLeft is the setting to change.OnTarget PC/TDS' Group variable identifies groups just within one file, whereas factor series is taken to number groups also across different original files. If your data was read with readDataOT1, readDataOT2 or readDataMisc, series is added automatically. For data from just one file, you can otherwise copy variable Groups to series in a data frame called shots with shots$series <- shots$Group.
If the data is missing information about the point of aim, (0,0) is assumed. If distance to target is missing, 100 is assumed.
In addition to the numerical results listed below, this function produces the following diagrams:
If package shiny is installed, an interactive web app for this functionality can be run with runGUI("analyze").
analyzeGroup,
getDistToCtr,
getMaxPairDist,
getMinBBox,
getMinCircle,
getCEP,
getMOA,
getRayParam,
drawEllipse,
anova.mlm,
ansari_test,
fligner_test,
wilcox_test,
kruskal_test
cmp <- compareGroups(DF300BLKhl, conversion='yd2in')
names(cmp)
cmp$ctr
cmp$meanDistToCtr
cmp$CEP
cmp$Kruskal
Run the code above in your browser using DataLab