data:image/png;base64,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

index1false

The Average is length2

data:image/png;base64,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

Sum of all items Read each item in the list Add it to "total" After traversal, show total "index" not important, can use "FOR each".Sum of all numbers = 2Average of all of numbers: Read each item in the list Add it to total After traversal, calculate average (total / # of items) "index" not important, so can use "FOR each". Contains negative?: Read each item in the list If item negative Say True stop traversal End if After traversal, Say False "index" not important, so can use "FOR each". Sorted?: Read each item except the last one If next item < item Say False stop traversal End if After traversal, Say True "index" is important, so must use "REPEAT" or "FOR index". Largest: largest = first item - 1 Read each item in the list If item > largest largest = item End if After traversal, Say largest "index" not important, so can use "FOR each". Sum of all numbers = 2Convert negative to abs: Read each item in the list If item negative Replace with abs of item End if After traversal show modified list "index" is important, so can use "repeat" or "FOR index".

Take even numbers: newlist = empty list Read each item in the list If item even Append item to newlist End if After traversal, show newlist "index" not important, so can use "FOR each". 213,23,11,4,9