Q1.
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 on guesswork? How can scientific thinking improve such predictions?
Answer
Judge any prediction by one test: could someone else check it with data you can both look at? If yes, it rests on evidence; if it rests only on a feeling, it is guesswork.
Sample answer: Before a one-day match, my uncle said “India will win, they always win at this ground.” That was partly evidence and mostly guesswork. It used one real pattern — home record — but ignored the playing conditions, who was injured, and which team was batting second.
Scientific thinking improves such a prediction in four steps:
- State it so it can be wrong. “India will win” is testable. “India will play well” is not, because nobody can agree when it has failed.
- Name the quantities that matter. Win record at that ground, average first-innings score, dew after sunset, bowling average of the opening pair.
- Use past data, not memory. If the last 20 matches at that ground were won 13 times by the side batting second, that is a measured 65% — a far better base than “they always win”.
- Check the outcome and revise. If the prediction fails repeatedly, the assumption behind it is wrong and must be changed, not defended.
Why it works: a prediction becomes scientific not because it turns out right, but because it is built from measurable quantities and can be shown to be wrong. A guess that happens to come true teaches you nothing, since you cannot tell which part of your reasoning did the work. A reasoned prediction that fails is genuinely useful — it points straight at the assumption that needs correcting, which is exactly how scientists use failed predictions.