Question

how can data be misinterpreted or be misleading? data can be misleading when people leave out important details or show numbers in graphs can also trick you if they stretch or shrink parts to make something look better

Explanation:

Data can be misinterpreted when important details are omitted, numbers are manipulated, or graphs are distorted (e.g., stretching/shrinking axes).

Answer:

Data can be misleading when people leave out important details, manipulate numbers, or distort graphs by stretching or shrinking parts.