Atomic number is the count of protons in the nucleus, and it uniquely identifies the element. The description that the atomic number is the number of protons and that this defines the element is the best choice because protons determine which element an atom is; isotopes share the same proton count but differ in neutrons, so their mass changes while their identity does not. The other options mix in neutrons, electrons, or total mass, which are not what defines the element: neutrons vary among isotopes, electrons change with charge, and total mass is protons plus neutrons. So the statement about the number of protons defining the element matches exactly what the atomic number represents.

Acidity on the pH scale is represented by values below 7. Since pH is a measure of hydrogen ion concentration, lower pH means higher acidity. The range from 0 up to 6 sits in the acidic region, with 7 being neutral and values above 7 being basic. So the part of the scale that is acidic is 0–6. The other options point to neutral (7), basic (8–14), or the entire range (0–14) which isn’t specifically acidic.

The concept here is how carbohydrates are categorized by the number of sugar units they contain. A polysaccharide is a long chain of monosaccharides linked together by glycosidic bonds. The prefix “poly-” means many, so polysaccharides are made of many sugar units, which is what “complex carbohydrates made of long chains of monosaccharides” describes. Examples include starch and glycogen for energy storage, and cellulose for structure. Monosaccharides are single sugar units; disaccharides are two linked sugars; proteins are made of amino acids, not sugars. That long-chain polysaccharide structure is what makes this the correct term.

The main idea here is how scientists move from noticing something to sharing what they’ve learned. You begin with careful observations of the natural world, because those observations ground your inquiry in real phenomena. From what you’ve seen, you form a question about what’s going on. Then you propose a testable explanation—a hypothesis—that can be evaluated. From that hypothesis you derive a prediction, a specific expectation you can check if the hypothesis is true. An experiment is designed to test that prediction and gather data. Finally, you publish the results so others can review, critique, and replicate the work. This sequence is the most logical flow: data first to spark questions, then a testable explanation, followed by predictions, experiments to test them, and communication of the findings. Starting with a question before any observation or starting with a hypothesis before collecting data would misplace steps, and skipping the reporting stage prevents scientific scrutiny and advancement.