Hi everybody
I come with question, hoping someone can give me some guidance.
This is may case.
Based under ISO , 9001, I´m starting to analyze data of production and want to
to get some values in average value.
In the case of analyzing days spent in production, I want to have a reference as a base, but
if I use an average value, it may result misleading.
this case, 10 work orders , one by one , days spent in production.
from 1 to 8 = 1 day, 1+1+1+1+1+1+1+1, but the 9 = 13 and 10 = 9
total sum of days is 30, divided by 10 = 3.
So average value for production is 3 days, which could be interpreted that sometimes
the work orders spend half a day, one day , while other times, 4 or 5 days.
But if we discard last two work orders (9 and 10), values could be = 1, which interpretation is very differente, we could say
Work orders spend half a day , while other times 1.5 days.
So in this case, which approach could be useful to adopt?
discard high values? how many, discard low values, how many?
Please what is recommended, I don´t have statistical experience, so have no idea what to do.
what criteria to use, to get a values more closer to reality.
Thanks
I come with question, hoping someone can give me some guidance.
This is may case.
Based under ISO , 9001, I´m starting to analyze data of production and want to
to get some values in average value.
In the case of analyzing days spent in production, I want to have a reference as a base, but
if I use an average value, it may result misleading.
this case, 10 work orders , one by one , days spent in production.
from 1 to 8 = 1 day, 1+1+1+1+1+1+1+1, but the 9 = 13 and 10 = 9
total sum of days is 30, divided by 10 = 3.
So average value for production is 3 days, which could be interpreted that sometimes
the work orders spend half a day, one day , while other times, 4 or 5 days.
But if we discard last two work orders (9 and 10), values could be = 1, which interpretation is very differente, we could say
Work orders spend half a day , while other times 1.5 days.
So in this case, which approach could be useful to adopt?
discard high values? how many, discard low values, how many?
Please what is recommended, I don´t have statistical experience, so have no idea what to do.
what criteria to use, to get a values more closer to reality.
Thanks