Statistics using binomial expansion

In summary, the conversation discussed the calculation of probabilities in a series of games between two evenly matched teams. There was some confusion about how to calculate the probabilities for games 6 and 7, but after further explanation and clarification, it was determined that the probabilities for each game were 50%. The conversation also touched on the importance of looking at the probabilities assuming each team wins the series, rather than just focusing on the overall probabilities for all possible outcomes.
  • #1
DODGEVIPER13
672
0

Homework Statement


Uploaded


Homework Equations


P(y)=(n c y)p^y(q^(n-y)) this is also uploaded


The Attempt at a Solution


My attempt at the first two parts is uploaded I am really confused on how to do game 6 and 7. Also I am a bit confused on how what I did worked in P(y=5), as the professor worked those parts out in class and I have forgotten since last class. Why is it 2 choose 1 is it because either team A or team B can win one game? Also why is it 4 choose 3, I am really lost on this part. So if I am assuming that they have played one game because the winning team has to win 4 total games, and the losing team has to win either game 1,2,3 or 4 and cannot win the last because the series would be over. Thus since they lost 1 they would have to play 4 more which is where the 4 on the top comes from, but why the three that would only be three wins thus they wouldn't win? Am I correct
 

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  • #2
DODGEVIPER13 said:

Homework Statement


Uploaded


Homework Equations


P(y)=(n c y)p^y(q^(n-y)) this is also uploaded


The Attempt at a Solution


My attempt at the first two parts is uploaded I am really confused on how to do game 6 and 7. Also I am a bit confused on how what I did worked in P(y=5), as the professor worked those parts out in class and I have forgotten since last class. Why is it 2 choose 1 is it because either team A or team B can win one game? Also why is it 4 choose 3, I am really lost on this part. So if I am assuming that they have played one game because the winning team has to win 4 total games, and the losing team has to win either game 1,2,3 or 4 and cannot win the last because the series would be over. Thus since they lost 1 they would have to play 4 more which is where the 4 on the top comes from, but why the three that would only be three wins thus they wouldn't win? Am I correct


Look at what happens when A wins the series; just multiply that probability by two because the teams are evenly matched. So, assume A wins in the following.

Suppose the playoffs last 4 games. Then A must win all 4; what is the probability of that?

Suppose the playoffs last 5 games. So, in the first 4 games, A must win 3 and B must win 1; then A wins game 5. What is the probability of that?

If the playoffs last 6 games, then in the first 5 games A must win 3 and B must win 2; then A must win game 6. What is that probability?

You can do it for 7 games.
 
  • #3
Ok so I get p(y=6)=.3125 and p(y=7)=.3125 did I do something wrong?
 
  • #4
A new attachment of what i have done so you can see clearly.
 

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  • #5
DODGEVIPER13 said:
Ok so I get p(y=6)=.3125 and p(y=7)=.3125 did I do something wrong?
If it's undecided still after 5 games, what must the score be? What two equally likely scores will there be after the 6th game?
 
  • #6
If its undecided after 5 it must be 3 games to 2 games. To win either team a or b must get 4 games to win so if team A has 3 going in the need to win for it be 6 and if team B has 3 going in they need to win for it to go 6. So what am I not seeing still?
 
  • #7
So it's 3-2. The next game will make it 4-2 or 3-3 equally likely. So what does that mean about the relative probabilities of there being 6 or 7 games altogether?
 
  • #8
DODGEVIPER13 said:
If its undecided after 5 it must be 3 games to 2 games. To win either team a or b must get 4 games to win so if team A has 3 going in the need to win for it be 6 and if team B has 3 going in they need to win for it to go 6. So what am I not seeing still?

In my first response I suggested you look at the playoff-length probabilities, assuming that A wins the series (then do the same, assuming that B wins). All such confusion would have been avoided if you had done that, but you chose to ignore the suggestion.
 
  • #9
So 50 chance of game 6 and 50 percent chance of game 7. All vickson I'm sorry I am just trying to figure this out it takes a bit for me to understand what may be obviously clear to you, I didn't mean to upset you.
 
  • #10
DODGEVIPER13 said:
So 50 chance of game 6 and 50 percent chance of game 7. All vickson I'm sorry I am just trying to figure this out it takes a bit for me to understand what may be obviously clear to you, I didn't mean to upset you.

I am not upset, just surprised. What I was attempting to do was to help you see things more clearly, not to confuse you. I do believe the approach you are using just makes things harder.
 
  • #11
So I have been told by about 4 people my answer is correct are they wrong, now I am really confused?
 
  • #12
DODGEVIPER13 said:
So I have been told by about 4 people my answer is correct are they wrong, now I am really confused?

Your answers are correct. I was addressing before a message you posted about being confused. If you are no longer confused, that's great.
 
  • #13
Ok sweet thanks man
 

Related to Statistics using binomial expansion

1. What is binomial expansion in statistics?

Binomial expansion is a mathematical process used in statistics to calculate the probability of getting a certain number of successes in a fixed number of trials. It involves expanding a binomial expression, which consists of two terms, to a higher power using the binomial theorem.

2. How is binomial expansion used in real life?

Binomial expansion is used in various real-life scenarios, such as predicting the outcome of a series of coin flips, calculating the probability of winning a certain number of games in a sports tournament, or estimating the likelihood of a certain number of defective products in a batch.

3. What is the formula for binomial expansion?

The formula for binomial expansion is (a + b)^n = ∑(n choose k) * a^(n-k) * b^k, where n is the number of trials, k is the number of successes, and a and b are the two possible outcomes with probabilities p and q respectively.

4. What is the difference between binomial expansion and binomial distribution?

Binomial expansion is a mathematical process used to calculate the probability of a specific number of successes in a fixed number of trials, while binomial distribution is a probability distribution that shows the likelihood of getting a certain number of successes in a given number of trials.

5. How can I use binomial expansion to solve problems in statistics?

You can use binomial expansion to solve problems in statistics by first identifying the number of trials and the probability of success in each trial. Then, you can use the binomial expansion formula to calculate the probability of getting a certain number of successes in those trials. This can be helpful in making predictions and analyzing data in various fields, including finance, economics, and psychology.

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