Entorn pensat per entrar en mode edició i modifcar l'operació que determinarà l'experiment de tirar dos daus "raros" (suma, distància, màxim i múltiplicació).
L'alumnat hi pot acotar la llista dels possibles resultats o el nombre de vegades que es fa l'experiment.
Si es clica en les puntes, es pot veure el resultat associat i la freqüència absoluta.
Junt amb el nombre total de tirades, l'alumnat es pot fer un idea de la seva probabilitat.
En el codi, i hi ha un apartat per poder fer casos particulars sense cap bloc de control associat.
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data:image/png;base64,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 la resta d'objectes (clons) baixant 13 pixelsExperiment tirar dos daus i sumar-los, repetir l'experiement molts vegadesbars-200-100400200returns a frequency analysis of the argument list, represented as a two-column table, where the first column contains the unique values and the second column their occurrencespt:$flash as frequências dos itens de _
pt:o agrupamento dos itens de _ de acordo com _
pt:uma ordenação de _ com critério _
pt:o histograma de _ entre _ e _ com intervalo _
1pt:o histograma de _ agrupado de acordo com _ entre _ e _ com passo _
add missing entries to a sorted list. Used for histogramspt:os itens de _ com a chave _ entre _ e _ com passo _ completados por _
11pt:a aplicação a _ de _
1pt:_ em minúsculas
pt:desenha gráfico de barras de _ em (x: _ , y: _ ) com largura _ e altura _
barsbars
lines
pie chart-200-10040020022100startsettingratio1step2lines0,0,10,0,24,0,41,0,29,36,13,52,0,80,0,50,9,28,30,0,51,0,34,0,13-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8,9,10,11,12122-3500-612