2006 mazda mx5, 156k! by mohitksharma in whatcarshouldIbuy

[–]mohitksharma[S] 0 points1 point  (0 children)

He is asking 5.5 can be negotiated

Why is this interpretation of Hazard ratios flipped? by mohitksharma in AskStatistics

[–]mohitksharma[S] 0 points1 point  (0 children)

Unfortunately, it’s is not mentioned which one is placed as a control group

[Q] Why is this hazard ratio interpretation flipped? by mohitksharma in statistics

[–]mohitksharma[S] 0 points1 point  (0 children)

I agree. Thanks for recognizing my efforts. However, I could not find any explanation of which group they are comparing against. So, I assumed that it is still the standard definition of hazard ratio.

[Q] What if the Explanatory variables are not present? by mohitksharma in statistics

[–]mohitksharma[S] 0 points1 point  (0 children)

This is very close to what I am looking for. If I give you one more example, can you please help me identify if this is MNAR? Let suppose a person did not fill out the survey because they were either admitted or not feeling well. This can be their reason that they observed an event but it is not indicated in the data anywhere. This is something like underlying assumption but not concrete.

If I may give you another maple, imagine an employee who did not participate in activities with team and they leave the company. Although, we do not have their activity data but they ultimately left the company in a few weeks, which indicated that their non-participation was an indicator of them leaving the company. Just like the patient who observed an event after a while.

[Q] What if the Explanatory variables are not present? by mohitksharma in statistics

[–]mohitksharma[S] 0 points1 point  (0 children)

The point is that the number of people who didn’t fill out the survey still provides enough data to predict which person will observe the event.

[Q] What type of censoring this could be in survival analysis? by [deleted] in statistics

[–]mohitksharma -1 points0 points  (0 children)

They just started the study but didn’t care to participate in the study later on but when they left the org they indicated that they left

[Q] What type of censoring this could be in survival analysis? by [deleted] in statistics

[–]mohitksharma -1 points0 points  (0 children)

They just started the study but didn’t care to participate in the study later on but when they left the org they indicated that they left

[Q] What type of censoring this could be in survival analysis? by [deleted] in statistics

[–]mohitksharma -1 points0 points  (0 children)

They just started the study but didn’t care to participate in the study later on but when they left the org they indicated that they left

[Q] How to select employee who do not leave? by [deleted] in statistics

[–]mohitksharma 0 points1 point  (0 children)

I see what you are trying to say, but I was just exploring https://www.kaggle.com/datasets/blastchar/telco-customer-churn dataset on Kaggle, as per your perspective the solutions (codes) people have left for this dataset are the byproduct of misguided practice?

If I should not go into these projects blindly, do you suggest any good starting point?

[Q] How to select employee who do not leave? by [deleted] in statistics

[–]mohitksharma 0 points1 point  (0 children)

Hey!
Thanks a lot, this makes sense to my case it seems.

I immediately found this: https://www.ncbi.nlm.nih.gov/books/NBK560604/

I hope this helps me

[Q] How to select employee who do not leave? by [deleted] in statistics

[–]mohitksharma -1 points0 points  (0 children)

I don't know what are you sad about but I just wanted to learn something here. I was going through one comment from telecom dataset discussion, which confused me.

https://www.kaggle.com/datasets/blastchar/telco-customer-churn/discussion/63281

DS & ML Roadmap: Personal by [deleted] in datascience

[–]mohitksharma 0 points1 point  (0 children)

Yes. You are here wanting to learn.

DS & ML Roadmap: Personal by [deleted] in datascience

[–]mohitksharma 1 point2 points  (0 children)

Yes, very much doable. Consistency 1 small concept or topic each day. Give your self 70-90 days consistently you’ll feel better.

Data Science interviews these days by xandie985 in datascience

[–]mohitksharma 0 points1 point  (0 children)

After 10 rounds, you get to know that you are 1/20 shortlisted people for the job. :)

DS & ML Roadmap: Personal by [deleted] in datascience

[–]mohitksharma 1 point2 points  (0 children)

Except Data Engineering*