data:image/png;base64,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

Should report the mean value for your data. With our sample data, this would return 94.47

LABEL 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!12

de:behalte Elemente, die _ aus _ ca:manté els elements on _ de _ es:mantener los elementos donde _ de _ fr:garder les items tels que _ de _ 1

de:kombiniere mit _ die Elemente von _ ca:combina amb _ els elements de _ es:combinar con _ los elementos de _ fr:combine avec _ les items de _ 1

de: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 _ _ 110i

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ 121

de: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 _ _ cont

de:wirf _ ca:llança _ es:lanzar _ fr:lance _ catchtag

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ cont

de:wirf _ _ ca:llança _ _ es:lanzar _ _ fr:lance _ _ catchtag

de: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 _ 110

de:wende _ an auf _ ca:mapeja _ sobre _ es:mapear _ sobre _ fr:appliquer _ à _ 1

Reports the Median - ours is 94.5

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]].

1111

Reports a new list containing the items of the input list, but in the opposite order.

1inputresult

Reports 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.

Reports 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#2

The 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.

#11datacountmapmany#

1data listscount

#1datacount1

Calculates the standard deviation. You do NOT need to alter this block.

This statistic is calculated by the (number of successes) / (total number of outcomes)

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,100653Jan11,99890Jan12,107012Jan13,177703Jan14,118460Jan15,119536Jan16,119461Jan17,118498Jan18,109623Jan19,109647118048.3114053.521116.229995195640.5