00:01
Once again, welcome to a new problem.
00:05
This time we're dealing with probability.
00:07
We're dealing with probability.
00:09
And for the most part, when you think about probability, this is your typical quantification.
00:17
This is quantification of chance processes.
00:24
So whenever you're dealing with probabilities, you're thinking about quantifying chance and probability of heads is one half and probability of tails is also one half.
00:39
So we are looking at a new problem.
00:43
And in this particular problem, we have a sales office.
00:48
So we have a sales office and it just so happens that this office has locations in dallas, seattle.
00:56
It also has a location in boston and it has a location in los angeles.
01:07
So the accounts receivable, the accounts receivable reveals the number of overdue invoices.
01:29
And the table shows the number of days that the invoices were overdue for the different offices that are presented in the particular problem.
01:49
So we have boston, we have los angeles, so we have all these offices.
01:56
And then under 30 days, we also have a single.
02:01
Sequence of 30 to 60 days, 30 to 60 days.
02:08
And of course, we have other frameworks, other days.
02:16
We have 61 to 90 days.
02:19
We also have over 90 days.
02:25
So we have 137, we have 85, we have 33, we have 18, we have 122.
02:37
We have 46.
02:38
We have 27.
02:40
We have 32.
02:42
We have 198.
02:45
We have 76.
02:47
We have 55.
02:49
We have 45.
02:51
We have 287.
02:52
We have 187.
02:53
We have 187.
02:55
We have 18.
02:57
66.
02:59
So, assuming, assuming, uh, we have 1 .9.
03:07
We have 4866.
03:07
Assuming storage of the invoices, so assuming storage of the invoices from a central, from a central database, then there are certain questions that we're going to respond, determine the probability, determine the probability that that randomly selected invoice from the database is from boston sales office...