When analyzing data, which does the scientist look for? a facts b patterns c opinions d predictions

When analyzing data scientists look for patterns, that help them form predictions.

Patterns are rules that variations/characteristics follow, either in data or anything else patterns might be used for.

Example:

The fact that worms are found always 10 meters forom eachother (not true, it's an example) is a pattern, that will help you predict the location of the next worm.

Hope it helped,

BioTeacher101

they both go up but then go back down. they both end lower than they started. lastly, they both are competitive/the second on.

explanation:

hey, i believe your answer would be d. sugar ribose and the base uracil. i believe this is the answer, because rna consists of sugar ribose, adenine, guanine, cytosine, and uracil.

your first option is incorrect, because that's dna. where it consists of sugar deoxyribose, adenine, guanine, cytosine and thymine.

your second option is also incorrect, this is because sugar deoxyribose is in dna, and uracil is in rna. these two do not make sense together.

your third option being incorrect, because sugar ribose is in rna, but not the base of thymine. rna consists of uracil, not thymine.

lastly your fourth option being correct! this answer is correct, because both sugar ribose, and the base uracil are in rna! ~

answer is d. sugar ribose and the base uracil.