Introduction to Statistics - Part 1

Introduction to Statistics - Part 1 (EST1)

This trai­ning imparts basic know­ledge of ele­men­ta­ry sta­tis­ti­cal methods. The con­tent is explai­ned in a prac­ti­cal man­ner and wit­hout exten­si­ve mathe­ma­ti­cal deri­va­tions. Ana­ly­sis methods and dia­gram forms are illus­tra­ted with examp­les. Simp­le flow charts faci­li­ta­te access to sta­tis­ti­cal test pro­ce­du­res.

Table of con­tent

• • Laws of pro­ba­bi­li­ty
  • Descrip­ti­ve sta­tis­tics
  • Pro­ba­bi­li­ty dis­tri­bu­ti­ons
  • Cen­tral limit theo­rem
  • t-test fami­ly
  • Chi-squa­re test fami­ly
  • F-test and ANOVA
  • Para­me­ter esti­ma­tes

Type
Our method trai­ning cour­ses are desi­gned to be soft­ware-inde­pen­dent and cross-sec­to­ral. We attach importance to a lively and inspi­ring atmo­sphe­re in the trai­ning and the­r­e­fo­re pre­sent examp­les from dif­fe­rent appli­ca­ti­on are­as, soft­ware can also be used.
The cour­se is open for dis­cus­sions and con­tri­bu­ti­ons from the par­ti­ci­pan­ts. Our trai­ners address all ques­ti­ons of the par­ti­ci­pan­ts and ans­wer them at the appro­pria­te point during the cour­se.
Par­ti­ci­pan­ts will recei­ve all trai­ning mate­ri­als as a PDF after­wards.

Key­words
ANOVA, descrip­ti­ve sta­tis­tics, chi-squa­re test, F-test, p-value, para­me­ter esti­ma­tes, signi­fi­can­ce, t-test, dis­tri­bu­ti­ons, pro­ba­bi­li­ty laws, pro­ba­bi­li­ty dis­tri­bu­ti­ons, cen­tral limit theo­rem

Pre­re­qui­si­tes
No pre­vious know­ledge is requi­red for this trai­ning. Basic know­ledge of mathe­ma­tics sim­pli­fies par­ti­ci­pa­ti­on.