data:image/png;base64,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:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeAAAAFoCAYAAACPNyggAAAOhUlEQVR4Xu3VwQkAAAjEMN1/abewn7jAQRC64wgQIECAAIF3gX1fNEiAAAECBAiMAHsCAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQIHLFxAWmhEwHPAAAAAElFTkSuQmCCShould 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 94.5Take 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)Jan 2013,90Feb 2013,100Jun 2013,130Sep 2013,150Mar 2014,200Dec 2014,300Sep 2015,400Jun 2016,500Dec 2016,600Apr 2017,700Sep 2017,800Jun 2018,1000414.1666666666667350292.84405216580530.41666666666666671029091.6666666667105084.0277777778,98700.69444444445,80750.69444444445,69784.02777777778,45867.36111111112,13034.027777777783,200.69444444444497,7367.361111111108,34534.027777777774,81700.69444444444,148867.3611111111,343200.694444444413