Pharma

Streamlining Stability Analysis: Tools and Techniques for Efficient Shelf-life Estimation in the Pharmaceutical Industry

Sta­bi­li­ty test­ing, also known as shelf-life assess­ment, stand as a pivo­tal stage in the phar­maceu­ti­cal deve­lo­p­ment, cru­cial for veri­fy­ing the iden­ti­ty, poten­cy and puri­ty of ingre­di­ents within a for­mu­la­ti­on. Phar­maceu­ti­cal sta­bi­li­ty is defi­ned as the abili­ty of a spe­ci­fic for­mu­la­ti­on within its desi­gna­ted con­tai­ner to main­tain con­for­mi­ty to its phy­si­cal and che­mi­cal pro­tec­ti­ve stan­dards. In […]

Statistica Webinar

Upgrade Your Analytics Practice

Would you like to learn more about the bene­fits of swit­ching from Mini­t­ab to Sta­tis­ti­ca? Join us for an enligh­tening web­i­nar, co-hos­ted with our estee­med part­ner Lui­gi Rog­gia from App­ly Sci­ence, whe­re we del­ve into the pivo­tal decis­i­on of tran­si­tio­ning from Mini­t­ab to Sta­tis­ti­ca and the pro­found impact it has on enhan­cing ana­ly­ti­cal and data sci­ence prac­ti­ces.

Statistica

The Statistica Story 

We, the com­pa­ny Stat­Soft and the soft­ware Sta­tis­ti­ca are clo­se­ly con­nec­ted and can look back at a long and exci­ting histo­ry.   It all began with the release of CSS (Com­ple­te Sta­tis­ti­ca Sys­tem) by Stat­Soft Incor­po­ra­ted in 1986, fol­lo­wed by a first DOS ver­si­on – now under the name STATISTICA in 1991. In the­se years the­re […]

Six Sigma Statistica

Six Sigma in Statistica 

What is „Six Sig­ma“? Six Sig­ma is a struc­tu­red, data-ori­en­­ted method to redu­ce defects, was­te and qua­li­ty issues of any kind in pro­duc­tion, ser­vices, manage­ment and fur­ther busi­ness acti­vi­ties.  Six Sig­ma is a trade­mark of Moto­ro­la, that shaped the term in the eight­ies. The method is based on a com­bi­na­ti­on of estab­lished tech­ni­ques of qua­li­ty assu­rance, […]

Machine Learning Statistica

Machine Learning in Statistica 

Machi­ne Lear­ning descri­bes a coll­ec­tion of algo­rith­ms that learn from data. This is useful to gain insights and to make pre­dic­tions. The­se algo­rith­ms can detect rela­ti­ons that were pre­vious­ly unknown to the users. Machi­ne Lear­ning con­ta­ins many dif­fe­rent algo­rith­ms, older and more recent ones, as well as com­plex and simp­le ones. Brief histo­ry les­son: Many of […]