As someone who has collected and analyzed real data for a
living, the idea of using simulated data for a Monte Carlo
simulation sounds a bit odd. How can you improve a real product
with simulated data? In this post, I’ll help you understand the
methods behind Monte Carlo simulation and walk you through a
simulation example using Companion by Minitab.
Companion by Minitab is a software platform that... Continue Reading
you ever tried to install ventilated shelving in a closet?
You know: the heavy-duty, white- or gray-colored vinyl-coated wire
shelving? The one that allows you to get organized, more efficient
with space, and is strong and maintenance-free? Yep, that’s the
one. Did I mention this stuff is strong? As in,
really hard to cut?
It seems like a simple 4-step project. Measure the closet, go
the... Continue Reading
shopping. For some, it's the most dreaded household activity. For
others, it's fun, or perhaps just a “necessary evil.”
Personally, I enjoy it! My co-worker, Ginger, a content manager
here at Minitab, opened my eyes to something that made me love
grocery shopping even more: she shared the data behind her family’s
shopping trips. Being something of a data nerd, I really geeked out
over the... Continue Reading
you regularly perform regression analysis, you know that
R2 is a statistic used to evaluate the fit of your
model. You may even know the standard definition of R2:
the percentage of variation in the response that is explained
by the model.
Fair enough. With Minitab Statistical Software doing all the heavy
lifting to calculate your R2 values, that may be all you
ever need to know.
But if you’re... 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
You run a capability analysis
and your Cpk is bad. Now what?
First, let’s start by defining
what “bad” is. In simple terms, the smaller the Cpk, the more
defects you have. So the larger your Cpk is, the
practitioners use a Cpk of 1.33 as the gold standard, so we’ll
treat that as the gold standard here, too.
Suppose we collect some data and run a capability analysis using
by Kevin Clay, guest blogger
In transactional or service processes, we often deal with
lead-time data, and usually that data does not follow the normal
Consider a Lean Six Sigma project to reduce the lead time
required to install an information technology solution at a
customer site. It should take no more than 30 days—working 10 hours
per day Monday–Friday—to complete, test and... 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
In Part 1 of this blog series, I
compared Six Sigma to a diamond because both are valuable, have
many facets and have withstood the test of time. I also explained
how the term “Six Sigma” can be used to summarize a variety of
concepts, including philosophy, tools, methodology, or metrics. In
this post, I’ll explain short/long-term variation and
between/within-subgroup variation and how they help... 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
Welcome to the Hypothesis Test Casino! The featured game of the
house is roulette. But this is no ordinary game of
roulette. This is p-value roulette!
Here’s how it works: We have two roulette wheels, the Null wheel
and the Alternative wheel. Each wheel has 20 slots (instead of the
usual 37 or 38). You get to bet on one slot.
What happens if the ball lands in the slot you bet on? Well,
that depends... Continue Reading
now I’m enjoying my daily dose of morning joe. As the steam rises
off the cup, the dark rich liquid triggers a powerful enzyme
cascade that jump-starts my brain and central nervous system,
delivering potent glints of perspicacity into the dark crevices of
my still-dormant consciousness.
Feels good, yeah! But is it good for me? Let’s see what the
Drinking more than 4 cups of coffee... 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
To make objective
decisions about the processes that are critical to your
organization, you often need to examine categorical data. You may
know how to use a t-test or ANOVA when you’re comparing measurement
data (like weight, length, revenue, and so on), but do you know how to compare
attribute or counts data? It easy to do with statistical software
One person may look at
this bar... Continue Reading
by Rehman Khan, guest blogger
There are many articles giving
Minitab tips already, so to be different I have done
mine in the style of my books, which use example-based learning. All
ten tips are shown using a single example.
If you don’t already know these 10 tips you will get much more
benefit if you work along with the example. You don’t need to
download any files to work along—although, if you... Continue Reading
Histograms are one of the
most common graphs used to display numeric data. Anyone who
takes a statistics course is likely to learn about the histogram,
and for good reason: histograms are easy to understand and can
instantly tell you a lot about your data.
Here are three of the most important things you can learn by
looking at a histogram.
Shape—Mirror, Mirror, On the Wall…
If the left side of a... Continue Reading
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