These questions appear inside the chapter itself, not at the end. The book page number is shown against each one so you can find it while reading.
Think of a prediction you or your family made recently (for example, the outcome of a cricket match). Was it based on evidence and reasoning, or mainly guesswork? How can scientific thinking improve such predictions?
A sample prediction. Before an India–Australia one-day match, my family predicted, “India will win today.” If we are honest, this was mainly guesswork — it came from hope and from remembering one or two exciting wins, not from looking at any real information. A prediction like this cannot be checked properly afterwards: if India loses, we simply say “bad luck”.
A scientific prediction is different. As the chapter says, predictions in science “are not guesses, they are reasoned expectations based on evidence and careful thinking.”
How scientific thinking would improve it.
The same thinking works for everyday predictions such as “it will rain today because the clouds look dark” — checking humidity, wind and past rainfall patterns turns a guess into a testable, reasoned prediction.
Describe one situation where an approximate answer is good enough, and one where you would need a very exact value.
Approximate answer is good enough — cooking rice for guests. If 15 guests are coming for dinner, we only need a rough estimate: about 75–100 g of rice per person, so roughly 1.5 kg in all. Being off by 100 g makes no real difference — a little rice is left over or a little more is cooked. An estimate is quick, uses easily available information and serves the purpose. (The chapter’s own example of estimating about 10,000 litres of air breathed in a day is of the same kind: the aim is a reasonable value, not an exact one.)
A very exact value is needed — the dose of a medicine. A doctor or pharmacist must measure a child’s medicine dose exactly, usually in milligrams worked out from the child’s body weight. Too little and the medicine will not work; too much and it can harm the child. Here even a small error matters, so careful, precise measurement is essential.
The idea behind the choice. How exact a value must be depends on what an error would cost. When a small error makes little difference, a quick estimate is sensible and saves effort. When a small error can cause harm, waste or failure — medicine doses, the amount of fuel for a space mission, the timing of trains on the same track, or the quantity of a chemical in a laboratory experiment — we need a very exact value.
Choose a real‑life object (maybe a pressure cooker or a mobile phone) or a problem (maybe a traffic jam near your school). Make a sketch listing what kind of ideas from physics, chemistry, biology, earth science, or mathematics are involved. Show how at least two branches of science connect with your example.
Chosen object: a pressure cooker. A sample sketch is shown below — your own sketch may list different ideas, which is perfectly fine.
Ideas from each branch.
How the branches connect. The physics idea (higher pressure raises the boiling point of water) gives a higher temperature, which speeds up the chemistry of cooking (starch and proteins break down faster), and the same high temperature serves biology by killing germs and making food easier to digest. Earth science joins in too: the low air pressure on mountains is the very reason a cooker is needed there. So one everyday kitchen object brings several branches of science together — just as the chapter says, the natural world does not have any such boundaries.
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