"Data! Data! Data! I can't make bricks without clay."
— Sherlock Holmes, in Arthur Conan Doyle's The Adventure
of the Copper Beeches
Whether you're the world's greatest detective trying to crack a
case or a person trying to solve a problem at work, you're going to
need information. Facts. Data, as Sherlock Holmes
But not all data is created equal, especially if you plan to
analyze as part of... Continue Reading
If you have a process that isn’t
meeting specifications, using the Monte Carlo simulation and
optimization tool in Companion by Minitab can help. Here’s how you,
as a chemical technician for a paper products company, could
use Companion to optimize a
chemical process and ensure it consistently delivers a paper
product that meets brightness standards.
brightness of Perfect Papyrus Company’s new... Continue Reading
Do your executives see how your quality initiatives affect the
bottom line? Perhaps they would more often if they had accessible
insights on the performance, and ultimately the overall impact, of
For example, 60% of the organizations surveyed by the American
Society for Quality in their 2016 Global State of Quality study say
they don’t know or don’t measure the financial...Continue Reading
Earlier, I wrote about the
different types of data statisticians typically encounter. In
this post, we're going to look at why, when given a choice in the
matter, we prefer to analyze continuous data rather than
categorical/attribute or discrete data.
As a reminder, when we assign something to a group or give it a
name, we have created attribute or
categorical data. If we count something,
like... Continue Reading
Everyone who analyzes data regularly has the experience of
getting a worksheet that just isn't ready to use. Previously I
wrote about tools you can use to
clean up and eliminate clutter in your data and
reorganize your data.
In this post, I'm going to
highlight tools that help you get the most out of messy data by
altering its characteristics.
Know Your Options
Many problems with data don't become... Continue Reading
You've collected a bunch of
data. It wasn't easy, but you did it. Yep, there it is, right
there...just look at all those numbers, right there in neat columns
and rows. Congratulations.
I hate to ask...but what are you
going to do with your data?
If you're not sure precisely
what to do with the data you've got, graphing it is a
great way to get some valuable insight and direction. And a good
graph to... Continue Reading
In my last post, I wrote about
making a cluttered data set easier to work with by removing
unneeded columns entirely, and by displaying just those columns you
want to work with now. But
too much unneeded data isn't always the problem.
What can you do when someone
gives you data that isn't organized the way you need it to be?
That happens for a variety of
reasons, but most often it's because the... Continue Reading
Isn't it great when you get a set of data and it's perfectly
organized and ready for you to analyze? I love it when the people
who collect the data take special care to make sure to format it
consistently, arrange it correctly, and eliminate the junk,
clutter, and useless information I don't need.
never received a data set in such perfect condition, you say?
Yeah, me neither. But I can... Continue Reading
People can make mistakes when they test a hypothesis with
statistical analysis. Specifically, they can make either Type I or
Type II errors.
As you analyze your own data and test hypotheses, understanding
the difference between Type I and Type II errors is extremely
important, because there's a risk of making each type of error in
every analysis, and the amount of risk is in your
if... Continue Reading
A recent discussion on the Minitab
Network on LinkedIn pertained to the I-MR chart. In the
course of the conversation, a couple of people referred to it as
"The Swiss Army Knife of control charts," and that's a pretty great
description. You might be able to find more specific tools for
specific applications, but in many cases, the I-MR chart gets the
job done quite adequately.
When you're... Continue Reading
Statistics can be challenging, especially if you're not
analyzing data and interpreting the results every day. Statistical
software makes things easier by handling the arduous
mathematical work involved in statistics. But ultimately, we're
responsible for correctly interpreting and communicating what the
results of our analyses show.
The p-value is probably the most frequently cited
statistic. We... Continue Reading
Have you ever wanted to know the odds of something happening, or
It's the kind of question that students are frequently asked to
calculate by hand in introductory statistics classes, and going
through that exercise is a good way to become familiar with the
mathematical formulas the underlie probability (and hence, all of
But let's be honest: when class is over, most... Continue Reading
People frequently have different opinions. Usually that's
fine—if everybody thought the same way, life would be pretty
boring—but many business decisions are based on opinion. And when
different people in an organization reach different conclusions
about the same business situation, problems follow.
Inconsistency and poor quality result when people being asked to
make yes / no, pass / fail, and... Continue Reading
Did you ever get a pair of jeans or a shirt that you liked, but
didn't quite fit you perfectly? That happened to me a few months
ago. The jeans looked good, and they were very well made, but it
took a while before I was comfortable wearing them.
I much prefer it when I can get a pair with a perfect fit, that
feel like I was born in them, with no period of
So which pair do you think I... Continue Reading
The language of statistics is a funny thing, but there usually
isn't much to laugh at in the consequences that can follow when
misunderstandings occur between statisticians and
non-statisticians. We see these consequences frequently in the
media, when new studies—that usually contradict previous ones—are
breathlessly related, as if their findings were incontrovertible
Similar, though less... Continue Reading
The line plot is an incredibly
agile but frequently overlooked tool in the quest to better
understand your processes.
In any process, whether it's baking a cake or processing loan
forms, many factors have the potential to affect the outcome.
Changing the source of raw
materials could affect the strength of plywood a factory produces.
Similarly, one method of gluing this plywood might be better... Continue Reading
A member of Minitab's LinkedIn
group asked how to create a chart to monitor change by
month, specifically comparing last year's data to this year's data.
My last post showed how to do this using an
Individuals Chart of the differences between this year's and
last year's data. Here's another approach suggested by a
participant in the group.
Applying Statistical Thinking
An individuals chart of the... Continue Reading
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