Basic level stats question?

Q)


Samplings: Students in Class. Suppose you are assigned the number 1, and each of the other students in your statistics class calls out consecutive numbers until each person in class his or her number. Explain how you could get a random sample of four students from your statistics class.


(a) Explain why the first four students walking into the classroom would not necessarily form a random sample.


(b) Explain why four students coming in late would not necessarily form a random sample.


(c) Explain why four students sitting in the back row would not necessarily form a random sample.


(d) Explain why the four tallest students would not necessarily form a random sample.





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Basic level stats question?
Q) How could you get a random sample? You can put the same numbers in a hat, and randomly draw four numbers. The corresponding students to those numbers would be a random sample.





a) The first four students walking in would not be a random sample because their numbers are consecutive, and one could predict the other three students in the sample, and therefore it wouldn't be "random" if you can predict the other members of the sample.





b) Four students coming in late would not be a random sample because the probability that a student will be absent is not the same for every student. That is to say that, some students are absent more than others, and you could also somewhat predict who might be absent on a particular day.





c) Four students sitting in the back row of a class are not a random sample, because they're being hand-selected. The back row would not be a random sample, not even if the students were required to sit in a new seat everyday, because there would be students more likely to sit in the back row than others (the trouble -makers who don't want to sit right in front of the teacher!)





d) The four tallest students wouldn't be a random sample, for the same reason as answer C - the four tallest students are not a random sample if they're being hand-selected. For example, if you wanted to know what students think is better. being taller or being shorter, and you select the four tallest students in the class to answer, then you'll obviously get biased results.