World Statistics Day Question 1: In your own work with data, what steps do you take to ensure that your data is trustworthy?

Question

World Statistics Day is 20 October 2020! It's a celebration of statistics and data that takes place every five years. This time, the theme is “connecting the world with data we can trust.”

We hope you’ll take part in this week’s discussions on statistics and data. The top 25 kudoed commenters will be eligible to receive the book "Invisible Women" by Caroline Criado Perez.

Question 1:

The theme of World Statistics Day 2020 is "connecting the world with data we can trust." In your own work with data, what steps do you take to ensure that your data is trustworthy?

Comment below with your response!

Please note: One book per JMP User Community member only. We can only send books to recipients within the United States and Canada. SAS staff not eligible.

Take the pledge! We’re asking data explorers to take a pledge with JMP to use trustworthy data to help connect the world. A badge will indicate to the Community your commitment to reliable data. jmp.com/statsday2020

KarenC · Answer

Lots of great answers already.  I will add, plot the data.  I like distributions, fit y by x (if I have groups to compare), and the multivariate scatter plots for starters.

louv · Answer

In my case measurement system and replication/verification. The physical manifestations of the handling in a chemical process does not lie.

P_Bartell · Answer

It took awhile...but during my tenure in industry...I was always trusting of the plan we articulated for the execution of a designed experiment was, in fact, what happened during execution, and to vehemently agree with @statman 's earlier reply, measurement of responses. Things like, randomization, blocking, did they really set the factors at the prescribed levels, any noticeable noise variables we didn't anticipate??? and on and on. Only after discovering that all too frequently our plan was NOT executed that I decided that to help with 'trustworthiness', I had to be present for experimental design execution and measurement work. Meant alot of long nights on 'C' shift, or learning new processes to ask the critical questions...but we ALL felt that our data was more trustworthy.

In the Toyota Production System there is a concept called 'Gemba'...which loosely translated means 'go to where the work is done and see.' That's what I tried to do.