experimental-design

How to experimentally determine the scheduling quantum of a process/thread?

阅读更多关于 How to experimentally determine the scheduling quantum of a process/thread?

Just to head off any comments to the effect of "why do you need to know this??": This is just a puzzle I was curious about, not something I need to do for any practical reason. Given a typical POSIX system[1], how would you design an experiment to determine the scheduling quantum[2] of a CPU-bound process? [1]: but NOT one that lets you query for this information through a syscall or /proc interface [2]: "Scheduling quantum" is defined as the amount of time a process will run on the CPU without blocking or yielding before its scheduled time is over and the OS lets a different process run. I'm

Assign control vs. treatment groupings randomly based on % for more than 2 groups

阅读更多关于 Assign control vs. treatment groupings randomly based on % for more than 2 groups

问题 Piggy backing off my own previous question python pandas: assign control vs. treatment groupings randomly based on % Thanks to @maxU, I know how to assign random control/treatment groupings to 2 groups; but what if I have 3 groups or more? For example: df.head() customer_id | Group | many other columns ABC 1 CDE 3 BHF 2 NID 1 WKL 3 SDI 2 JSK 1 OSM 3 MPA 2 MAD 1 pd.pivot_table(df,index=['Group'],values=["customer_id"],aggfunc=lambda x: len(x.unique())) Group 1 : 270 Group 2 : 180 Group 3 : 330

订阅 experimental-design