Spotfire Statistica Data Science Author

Spot­fi­re Sta­tis­ti­ca Data Science Aut­hor offers the full ran­ge of sta­tis­ti­cal methods, data import, export and pre­pa­ra­ti­on, visua­li­sa­ti­ons and report­ing, sup­ple­men­ted by machi­ne lear­ning and many other func­tions. The sta­tis­ti­cal methods offe­red in Spot­fi­re Sta­tis­ti­ca Data Science Aut­hor include descrip­ti­ve sta­tis­tics, regres­si­on ana­ly­sis, ANOVA/MANOVA, non-para­me­tric methods, indus­tri­al sta­tis­tics, design of expe­ri­ments, SPC, power ana­ly­sis and much more. Machi­ne Lear­ning (ML) inclu­ding arti­fi­ci­al neu­ral net­works, sup­port vec­tor machi­nes and decis­i­on trees, methods for fea­ture sel­ec­tion, clus­ter ana­ly­sis, weight of evi­dence reco­ding, shop­ping bas­ket ana­ly­sis using asso­cia­ti­on rules, text mining, sta­bi­li­ty (shelf life), a busi­ness rule engi­ne, respon­se opti­mi­sa­ti­on, model code gene­ra­tor, PI con­nec­tor and much more. Ana­ly­ti­cal pro­ces­ses can be visual­ly struc­tu­red, auto­ma­ted and reu­sed via the pro­ject inter­face. In addi­ti­on to the exis­ting exten­si­ve opti­ons, seam­less cal­cu­la­ti­ons from R or Python envi­ron­ments can be inte­gra­ted.