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#1 Re: Help Me ! » Predictions based on history data » 2009-06-03 19:59:20
Hmm.. Actually the data I posted was just an example, there is no real data set.
If you think it helps to see a variation in column 2 as well please feel free to assume. E.g.:
Date working hrs % work
1 8 80
2 2 30
3 4 60
4 10 100
5 8 70
.....
PS: If I can manage somehow to observe the time taken for completing 100% work everyday, then using prob density function I can plot the distribution and then it's possible to anwer my question for any probability. But of course in my scenario I don't have that data.
#2 Re: Help Me ! » Predictions based on history data » 2009-06-03 02:50:49
Interesting you say that. I started off with a simple average and then moved onto std deviation. But couldn't really make any headway. Here is what I did so far. My basic problem is how to factor in the probability.
1. I started with a simple technique:
Calculate the average efficiency based on history:
D=N
e = [ ∑ ( Wd / Hd ) ] / N
D=1
Where
- Wd is %work done on day d.
- Hd is number of working hours on day d.
- N is total number of days for which history is available.
Now I can predict the number of hours needed (100 * e) to complete 100% of work ONLY WITH 100% probability. So I don't know how to factor in the probability.
2. I tried plotting the std deviation of % work done. I didn't really get much further. I simply don't know how to factor in the probability value as the plotted data only considers % of work done as dimension. Also in this case I don't see even the time playing any role, i.e. I don't see the correlation between std deviation graph and time dimension.
#3 Help Me ! » Predictions based on history data » 2009-06-02 23:14:15
- thekashyap
- Replies: 5
Hi,
My problem is to come up with a method to predict based on history data. Here is the problem:
I'm observing the % of work finished by a single employee everyday during working hours. E.g. if the employee is a postman, the employee is expected to deliver 100 letters to appropriate addresses every day then % work indicates how many letters were actually delivered during working hours. So my history data looks something like this:
Date Working hrs % work
01-Jan 8 95
02-Jan 8 50
03-Jan 8 80
04-Jan 8 40
05-Jan 8 60
... ... ...
28-Feb 8 75
I need to come up with some formula / way by which based on this history data I can answer following question:
- What is the number of working hours needed to be X% sure (e.g. 95% probability) that employee would complete 100% work.
- If number of working hours is X then how much work is the employee likely to finish.
Could someone point me in the right direction ? We are currently trying to employ some technique but not much luck yet. I don't mention which technique to avoid influencing. 
Thanks
Kashyap
PS: Reason to put working hours in input data although it's constant is because for different employees it could very.
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