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1. ### Sets and Events

Thank you. It's very annoying to have books like this. My Introduction to Probability and Statistics is filled with typos. It's horrible to be introduced to Probability with textbooks like this.
2. ### Sets and Events

I have a problem that is suppose to be very basic, but it's hard for me to understand. Problem: Two dice are thrown. Let E be the event that the sum of the dice is odd; let F be the event that at least one of the dice lands on 1; and let G be the event that the sum is 5. Describe the events EF...
3. ### Verify and Explain Binomial R.V. Identities

I understand: But, I do not understand this part: I know by one of the identities that P(Y=n-k) = P(X=k), but I don't know from where do you get the rest.
4. ### Estimate Deaths per Week

In the 1980s, an average of 121.95 workers died on the job each week. Give estimates of the following quantities: a.) the proportion of weeks having 130 deaths or more; b.) the proportion of weeks having 100 deaths or less. Explain your reasoning. Procedure I'm not sure, how to start...
5. ### Verify and Explain Binomial R.V. Identities

What do you mean by " the end"? I know that P{Y>=n-k} has to be described as 1-P{Y=0}-...-P{Y=n-k-1} Could you develop further on what you said?
6. ### Verify and Explain Binomial R.V. Identities

From what I posted originally: If X and Y are binomial random variables with respective parameters (n,p) and (n,1-p), verify and explain the following identities: a.) P{X<=i}= P{Y>=n-i}; b.) P{X=k}= P{Y=n-k} I have proven part b.) and yes it's the same. How do I prove part a.)...
7. ### Verify and Explain Binomial R.V. Identities

I know that * p and 1-p * are complement of each other, but how does this help me?
8. ### Verify and Explain Binomial R.V. Identities

What do you mean by opposite order?
9. ### Verify and Explain Binomial R.V. Identities

If X and Y are binomial random variables with respective parameters (n,p) and (n,1-p), verify and explain the following identities: a.) P{X<=i}= P{Y>=n-i}; b.) P{X=k}= P{Y=n-k} Relevant Equations: P{X=i}=nCi *p^(i) *(1-p)^(n-i), where nCi is the combination of "i" picks given "n"...