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data:image/png;base64,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90-70-20200120-40-20100120-40-200120itemShould report the mean value for your data. With our sample data, this would return 94.47LABEL will stamp text on the stage at the given font size. The direction of the text is the direction the sprite is facing, and color will match the pen color.de:drucke _ in Größe _
ca:etiqueta _ de mida _
es:etiqueta _ de tamaño _
fr:étiquette _ d'une taille de _
Hello!12de:behalte Elemente, die _ aus _
ca:manté els elements on _ de _
es:mantener los elementos donde _ de _
fr:garder les items tels que _ de _
1de:kombiniere mit _ die Elemente von _
ca:combina amb _ els elements de _
es:combinar con _ los elementos de _
fr:combine avec _ les items de _
1de:wenn _ dann _ sonst _
ca:si _ llavors _ si no _
es:si _ entonces _ sino _
fr:si _ alors _ sinon _
de:für _ = _ bis _ _
ca:per _ = _ fins _ _
es:para _ = _ hasta _ _
fr:pour _ allant de _ à _ _
110ide:füge Wörter zusammen _
ca:uneix les paraules _
es:unir las palabras _
fr:fusionne les mots _
121de:Liste $arrowRight Satz _
ca:llista $arrowRight frase _
es:lista $arrowRight frase _
fr:liste $arrowRight phrase _
de:Satz $arrowRight Liste _
ca:frase $arrowRight llista _
es:frase $arrowRight lista _
fr:phrase $arrowRight liste _
de:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
cont3de:wirf _
ca:llança _
es:lanzar _
fr:lance _
catchtagde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
catchtagde:für jedes _ von _ _
ca:per cada _ de _ _
es:para cada _ de _ _
fr:pour chaque _ de _ _
de:falls _ dann _ und pause $pause-1-255-220-0
ca:si _ fes _ i atura-ho tot $pause-1-255-220-0
es:si _ haz _ y páralo todo $pause-1-255-220-0
fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0
de:Wort $arrowRight Liste _
ca:paraula $arrowRight llista _
es:palabra $arrowRight lista _
fr:mot $arrowRight liste _
de:ignoriere _
ca:ignora _
es:ignorar _
fr:ignore _
de:Liste $arrowRight Wort _
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1Take any number of input lists, and create a new list containing the items of the input lists. So
APPEND [A B] [C D]
where the [,,,] are lists reports the list
[A B C D]
not [[A B] [C D]].11111Reports a new list containing the items of the input list, but in the opposite order.1inputresultReports a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the last one is kept in the result.1Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.1even itemsmerge11#1#2The second input is an "association list," a list of two-item lists. Each of those smaller lists has a "key" as its first item and a "value" as its second. ASSOC reports the first key-value pair in the association list whose key matches the first input.11#11datacountmapmany##1#1data listscount#1datacount1Calculates the standard deviation. You do NOT need to alter this block.This statistic is calculated by the (number of successes) / (total number of outcomes)2011,230.162012,248.742013,251.302014,256.822015,258.092016,259.292017,260.692018,261.502019,265.912020,268.09256.059258.6910.271101644906450.418.580000000000013,2.5600000000000023,5.519999999999982,1.2699999999999818,1.2000000000000455,1.3999999999999773,0.8100000000000023,4.410000000000025,2.179999999999954.214444444444442