Hello @katxt ,
The main point here is that I want to calculate an overall risk score which represents all transactions risks fairly. Like I mentioned previously, weighted average method seems fair at first sight. But with this calculation, the impact of the high risk transactions types 1 and 3...
I have a couple of transaction types with different risk scores in a scale between 0 to 10 [0-10]:
Trans_type_1_risk = 8 and Number_of_trans_type_1 = 1.000.000 (~0.04% of Total_nbr_of_transactions)
Trans_type_2_risk = 4 and Number_of_trans_type_2 = 1.000.000.000 (~40% of...
Sorry @Karabiner , I forgot to mention that my sample size is actually total 1300 aggregated rows (600 with Yes and 700 with No), I just shared here a made-up sample. In that case, is there a way of calculating the "importance of feature" and doing a test like t-test?
Important note: I will do the processes below with ready functions/packages in tools, and I am not a professional statistician, so I would really appreciate if you can help with the question below with simplified explanation.
I have a dataset with a couple of features as "Product Risk...
@hlsmith thank you for your answer. How did we populate the data? Maybe you expect an answer like "some statistical reference data", but this problem is related to an area which doesn't have enough data, but it has lots of law, regulation which consists of qualitative rules instead of...
I have a set of population with multiple risk factors:
- Every population member can have a combination of 30 different risk factors.
- Every risk factor can have a score from 0 to 10 depending on population members' characteristic.
- So for example,
-Member-1 can have 4 risk...
I am a complete newbee in R, and I have a problem with linear trend fitting.
My data is daily financial data for around 4 years. The financial year is 260 days (5 days a week) so the total amount of data is 913.
For the simplicity, the data is only one cloumb with 913 data and with one...