Bernoullijeva shema na testovima

Testove sa zadatcima višestrukog izbora i određivanja vjerojatnosti pogađanja određenog broja točnih odgovora možemo promatrati kao određivanje vjerojatnosti kod ponavljajućih pokusa po Bernoullijevoj shemi. Uzmimo za primjer test na kojem su tri zadatka, a u svakom zadatku tri ponuđena odgovora: [i]A[/i], [i]B[/i] i [i]C[/i]. Svih 27 načina na koje možemo dati odgovore na tri zadatka dani su na slici:[br][img 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[/img][br]Pretpostavimo da je točan odgovor na svako od tri zadatka [i]A[/i].[br][list][*]Vidimo da je vjerojatnost točnog odgovora na sva tri zadatka [math]\frac{1}{27}[/math].[/*][*]Na 6 različitih načina može se točno odgovoriti na dva zadatka pa je vjerojatnost tog događaja [math]\frac{6}{27}=\frac{2}{9}[/math].[/*][*]Na 12 različitih načina može se točno odgovoriti točno na jedan zadatak pa je vjerojatnost tog događaja [math]\frac{12}{27}=\frac{4}{9}[/math].[/*][*]Na 8 različitih načina može se pogrešno odgovoriti na sva tri zadatka pa je vjerojatnost tog događaja[math]\frac{8}{27}[/math]. [br][/*][/list]Vjerojatnosti tih događaja mogli smo izračunati po Bernoullijevoj shemi: [math]p \left(A\right)= \binom{n}{k}\cdot p^k \cdot (1-p)^{n-k}[/math].[br]Ovdje je [i][b]n[/b] [/i]broj pokusa odnosno zadataka testa, [i][b]k[/b][/i] broj povoljnih ishoda (točnih odgovora) i [i][b]p[/b][/i] vjerojatnost povoljnog ishoda. [b]1[/b][i][b]-p[/b][/i] je vjerojatnost suprotnog događaja, u slučaju testova netočnog odgovora.[br][br][b]Uputa za uporabu interaktivnog kalkulatora [/b]za izračun vjerojatnosti po Bernoullijevoj shemi. U tekstualna polja upišite tražene elemente i pritisnite tipku [i][b][color=#ff0000]Enter[/color][/b]. [/i]Razlomak možete pisati npr. kao 1/3.

Information: Bernoullijeva shema na testovima