data:image/png;base64,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data:image/png;base64,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Should 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 _
ca:llista $arrowRight paraula _
es:lista $arrowRight palabra _
fr:liste $arrowRight mot _
de:Zahlen von _ bis _
ca:nombres des de _ a _
es:números de _ a _
fr:nombres de _ à _
1101de:wende _ an auf _
ca:mapeja _ sobre _
es:mapear _ sobre _
fr:appliquer _ à _
1Reports the Median - ours is 94.5You need to update. How do you get the middle value? What if the list is of even length? Odd length?Take 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)2005,73632006,88962007,106842008,115672009,111282010,111312011,107872012,110452013,114572014,119622015,125212016,131722017,139302018,146062019,150411168611512108.101803870240760.8666666666666667