what is the difference between a biased sample and a biased question

A biased sample is not a true sample of the population at large. For instance, a biased sample may include mostly women or mostly people under age 25.

A biased question reflects the questioner's viewpoint. This site gives examples of biased questions.

http://www.calvin.edu/~rpruim/courses/libarts-stats/I00/overheads/biased.shtml

a biased coin with P(H)=1/4 and P(T)=3/4 is thrown twice, find the probability of getting two heads

A biased sample refers to a subset of a larger population that does not accurately represent the characteristics of the entire population. This occurs when certain individuals or groups are overrepresented or underrepresented in the sample, leading to results that may not be generalizable.

To recognize if a sample is biased, you need to understand how the sample was selected. Sampling methods such as random sampling or stratified sampling help to minimize bias. For example, if a survey is conducted to understand public opinion about a political issue, but only one specific demographic group is surveyed, the results would not be representative of the entire population.

On the other hand, a biased question refers to a question that is framed in a way that influences or manipulates the respondent's answer. Biased questions can be unintentional, resulting from poor question formulation or the use of leading language that steers respondents toward a particular response.

To identify a biased question, you need to consider the wording and structure of the question. Look for loaded language, leading statements, assumptions, or anything that may introduce a bias favoring a particular answer. For instance, if you ask, "Don't you agree that this policy is unfair?" you are assuming the person agrees and introducing a bias in the question itself.

Both biased samples and biased questions can introduce distortions and inaccuracies into research and data collection processes. To mitigate bias in samples and questions, it's essential to employ proper sampling methods and carefully construct neutral and unbiased questions.