I’m stuck on what actually counts as the “sample space” in simple probability problems. I keep flip-flopping between listing every tiny outcome and grouping them into bigger buckets, and then my probabilities wobble. My brain wants tidy buckets; math seems to want microscopic detail. I’m trying to reconcile these two vibes.
Example 1: rolling two fair dice and looking at the sum. If I write the sample space as all ordered pairs, S = {(1,1), (1,2), …, (6,6)}, then I’m fine: there are 36 equally likely outcomes, and the event “sum = 7” is E = {(1,6), (2,5), (3,4), (4,3), (5,2), (6,1)}. That gives 6/36, which I know is right.
But sometimes I get lazy and I write the sample space as just the possible sums S’ = {2,3,4,5,6,7,8,9,10,11,12}. Then my gremlin brain tries to do P(sum = 7) = 1/11 because 7 is one of 11 outcomes, which I know is wrong. So… is S’ a valid sample space at all? If so, do I have to attach different probabilities to each sum and stop doing naïve counting? Or is there some rule of thumb that says I should prefer a sample space where all outcomes are equally likely whenever I plan to count? That “equally likely” part is exactly where I keep slipping.
Example 2: drawing two marbles from a bag without replacement. Say the bag has 3 red (R) and 2 blue (B). If I go detailed: S = {RR, RB, BR, BB} (I’m treating order as different because of the without-replacement part), and then the event “exactly one red” is {RB, BR}. That feels okay. But if I decide I don’t care about order and switch to the coarser S’ = {2R, 1R1B, 0R}, my instinct was to say P(1R1B) = 1/3 because it’s one of three outcomes, and I can hear the math gods facepalming. I think the trouble is that the three elements in S’ aren’t equally likely. Am I thinking about this the right way? Is it “legal” to use the coarser sample space as long as I remember to weight the outcomes properly? Or should I always build the fine-grained sample space first and then define events by grouping outcomes?
I think my main confusion is: what makes something an “elementary outcome”? Is it “what physically happens” (ordered stuff), or “what the question observes/records” (like just the sum or the counts)? If a problem only cares about the multiset of colors or the sum of dice, should I change the sample space to those objects, or keep the detailed one and define an event that lumps outcomes together? Follow-up question: is there a standard or preferred way to set this up to avoid mistakes, especially when outcomes aren’t equally likely?
If someone could explain how to choose a sample space on purpose (instead of me guessing and then tripping over the counting), and how that choice affects whether I can just count vs. needing weights, I’d be super grateful. And if my partial attempts above are on the right track, could you point out where I’m nearly there vs. where I’m off?