On Data Integrity and Cleaning

This year I hired a Quickbooks consultant to bring my bookkeeping up from the stone age.  (I had been using Excel).

She had asked for some documents with detailed data, and I tried to send her something else as a shortcut.  I thought it was detailed enough. It wasn’t, so she just fudged it. The bottom line was all correct, but the data that put it together was all wrong.

I hit the roof.Internally, only—I realized it was my own fault for not giving her the info she needed.  She did a fabulous job.

But I could not leave the data fudged, even if it all added up to the right amount, and already reconciled. I had to go in and spend hours fixing it. Truthfully, I was a bit of a compulsive nut about it.

And then I had to ask myself why I was so uptight—if accountants think the details aren’t important, why do I? Statisticians are all about approximations and accountants are exact, right?

As it turns out, not so much.

But I realized I’ve had 20 years of training about the importance of data integrity. Sure, the results might be inexact, the analysis, the estimates, the conclusions. But not the data. The data must be clean.

Sparkling, if possible.

In research, it’s okay if the bottom line is an approximation.  Because we’re never really measuring the whole population.  And we can’t always measure precisely what we want to measure.  But in the long run, it all averages out.

But only if the measurements we do have are as accurate as they possibly can be.


The Pathway: Steps for Staying Out of the Weeds in Any Data Analysis
Get the road map for your data analysis before you begin. Learn how to make any statistical modeling – ANOVA, Linear Regression, Poisson Regression, Multilevel Model – straightforward and more efficient.

Reader Interactions


  1. Ursula Saqui Ph.D. says


    This post made me smile. I would have done the exact same thing! I can’t stand something not being right even if it turns out okay in the end. I think this compulsiveness and obsessiveness in research and stats is a very good thing and helps our field maintain its integrity.

Leave a Reply

Your email address will not be published. Required fields are marked *

Please note that, due to the large number of comments submitted, any questions on problems related to a personal study/project will not be answered. We suggest joining Statistically Speaking, where you have access to a private forum and more resources 24/7.