
Wizard for Mac – new kind of statistics program - deathtrader666
http://www.wizardmac.com/
======
incongruity
Generally speaking, IMHO, making the _interface_ easier, in practice, doesn’t
actually make _using statistical methods correctly_ easier and that’s scary.

SPSS is a classic example - and the social sciences have had a series of
discredited papers over recent years due to poor application of statistical
methods. Just because you can put a dataset in and get values out - even
values that _look_ significant, it doesn’t mean they are - did all of the
assumptions and requirements of the methods/tests you used hold true/pass with
your data?

So, while I haven’t looked closely at this tool, all I saw was talk of the
interface and the ease of getting results even if “you don’t know where to
start”. That scares me. Especially when you start talking about applications
in domains like medicine. That could be lives in the balance. Would we want
civil engineers using tools like this to build bridges? Or people designing
nuclear reactors?

To me, this is worse, not better unless it somehow helps you actually
understand when, why and how to correctly use these tools.

~~~
wanderfowl
Agreed. It's odd to charge money for this at all, given that there are such
robust statistical tools for free (read: R). But on top of what you said, the
fact that trial versions can't export p-values is tacit endorsement of the "p
< 0.0x is all that matters" camp, further promoting toxic statistical
thinking.

Promoting ease of use of tools and simplification of harder problems is great,
but this is a really, really dangerous thing to make easy and oversimplified.

Nope nope nope nope nope.

~~~
wenc
To be fair, R isn't really that accessible to most social scientists. Heck, R
isn't really that accessible to most programmers either. The tidyverse and R
notebooks have definitely improved things by leaps and bounds, but R at its
core is an unusual language. (I say this as a somewhat proficient R user) Its
programmatic nature does aid in coming up with reproducible data analyses
though.

SPSS has, shall we say, a less than savory reputation.

All this to say that there is a market for something much friendlier than R. R
is used by pure statisticians, data scientists and the like, but most social
scientists prefer Stata, which has pretty legit statistical routines as well
as a point-and-click UI.

~~~
Fomite
I'm fairly fond of JMP, which in my mind manages to thread the gap between
"Easy UI" and "Push buttons until you get a p-value" decently.

~~~
singingfish
Yeah I quite like JMP. JMP for the easy routine stuff. R for when shit gets
real. I don't do much stats these days though, so not having a JMP license, I
just reach straight for R on the rare occasions I need it.

------
devin
I own a copy of Wizard and have found it valuable on numerous occasions from
digging around databases to tinkering with models. It handles non-trivial
amounts of data with relative ease, allows you to do joins in the UI, has nice
graphical representations that can change based on the type of the column. The
list goes on. It does quite a lot of stuff.

Everyone I show this software to goes: "Whoa, what is this?" I would recommend
checking it out before dismissing it.

~~~
vatys
I use Wizard all the time at work for analyzing manufacturing data to quickly
check for trends and correlations. I find it better, easier, and faster than
the internal tools purpose-built for the same task. I also prefer Wizard over
JMP, Tableau, or any R/numpy/gnuplot methods, specifically for one-off tasks
and analyzing new issues.

I’m not going to write a script or configure complex software for a quick
check. Wizard is perfect for that. It’s also super fast at scanning through
really enormous CSV files, then generating plots for every parameter.

Every coworker who sees me using it for these tasks wants to know what it is,
or how I send out relevant plots so quickly when new datasets are available.
It’s really a fantastic tool for quick work.

There seems to be a lot of negativity in this comments section about misuse of
statistics. I think people are missing the point. Easy tools make data
analysis more accessible, but misuse of data is the fault of the user, not the
tool.

~~~
mnky9800n
I some how cannot read these positive comments without believing that they are
AstroTurf.

------
haZard_OS
Robust statistical analyses require knowledge, judgement, and increasingly,
specialist expertise. To market a product as a way to jettison the
statistician is so shortsighted as to be intellectual malpractice.

Forgive me if I seem overly aggressive but I have grown weary of my and my
colleagues' profession being side-lined and belittled. Politicians,
administrators, and even some other scientists see statistics as merely a
badge to be placed atop their own work for validation. Well, ladies and
gentlemen, statistics is more than that. It is an empirical science in its own
right.

    
    
      Of course, it doesn't always take a statistician to do the necessary statistical work. I am no physicist yet I can certainly apply the Clausius Clapeyron equation as needed. Likewise, I expect many (perhaps most) scientists to be able to apply an ANOVA or simple regression as the need arises.
    
      HOWEVER, the lack of intellectual humility on the part of so many non-statisticians when applying statistical tools to their own work is maddening.

~~~
mbell
I'm having a hard time understanding how statistics could be considered an
empirical science, and really what bearing that term has on statistics at all.
Can you explain?

~~~
closed
Not OP, but I would say that when statistics acts like a subfield of
mathematics, then it is an art.

However, if we consider judging whether a statistical method will be useful
for the world as a part of statistics, then that part sometimes is an
empirical science.

That is, the statement "I should use X technique because it performs Y% well"
is sometimes an an empirical statement.

------
ljw1001
I don't understand the hostility to this application. Progress comes from
trying different ways to do things. I tried this program a few years back, and
thought it was ok. It is easier to use than JMP, which some others have
mentioned, though not as powerful.

There is nothing about easy-to-use that precludes understanding, and certainly
nothing about difficult-to-use that promotes it. They are largely orthogonal.
Using R doesn't make you a statistician, any more than using C++ makes you a
software engineer. If anything, a simple interface can reduce the number of
ways you can shoot yourself, and leaves more time to focus on the problem.

Being easy-to-use may be the difference between some analysis and no analysis,
or at best, analysis by spreadsheet.

And finally, this is Hacker News. The author wrote this software and makes
some money off it. Great. Isn't that what this place is all about?

~~~
csomar
I can see a 1.000 ways I can use this app. R is cool and stuff but it is very
hard to get any chart if you don't know the language. And it might take a
while to write down any code.

This is much simpler. You just input the data and it gives you charts right
away.

------
trevvr
Wizard is an awesome tool for initial investigation and initial slicing and
dicing of incoming data. For trying out ideas and seeing if what you're
"seeing" in the data might be worthy of further investigation and hypothesis
testing.

It isn't R, SPSS or Minitab. It's brilliant at what it does and I love it.
I've been using it for 3 / 4 years and wouldn't swap it for any other tool.

------
leemailll
I don't understand this program. It states it is a statistics program but on
the front page only test stated is " Shapiro-Wilk". I don't know how many here
are familiar with statistics, but that is basically the hello-world thing for
statistic tests. Also the pricing puts this program directly at the range of
Graphpad's Prism, which is widely-used in academic fields other than the field
of statistics, and quite intuitive.

Making good-looking figures nowadays is not a selling point anymore. If one's
willing to script rather than clicking-the-mouse, Prism, Igor Pro, Origin Pro,
Matlab (pricing from low to high) all can produce great figures and solid
statistical test for people out of the statistics field. But nothing these
days beats R for versatile of statistical tests.

------
untangle
If you are willing to defer dismissing this tool out of hand as a p-value
generator, you can get a better feel for how the author (Evan Miller) thinks
about stats from his web site [1] and a presentation he gave [2]. I think
you'll find that "Wizard" is not the product of whimsy.

[1] [http://www.evanmiller.org/](http://www.evanmiller.org/) [2]
[https://www.youtube.com/watch?v=TzJMFxj7GRI](https://www.youtube.com/watch?v=TzJMFxj7GRI)

------
cwyers
> Trial versions never expire. They do not report p-values, and cannot save or
> export. Requires OS X 10.10 or later.

Maybe this makes the trial versions better?

------
ACow_Adonis
Apart from being literally the opposite of where I think statistics should be
headed (i.e. I see the notion of "removal of 'complicated statistics
knowledge'" to be more dangerous than helpful), I also had some practical
feedback from watching the 12 minute intro video.

-Firstly, how does the visualization know the respective population or sample size from which the summary statistics and intervals are to be drawn?

\- The demo used a pie chart to try to display summary stats and confidence
intervals from the general social survey. Aside from professional
statisticians general dislike of pie charts, you cannot plot confidence
intervals in this way into a pie chart just by inserting 'more white space
between the slices'. There's only 100% of the area of the circle that you've
got to play with, so any attempt to increase the 'white space' between the
slices necessarily warps the real estate remaining to represent each actual
slice.

\- Honestly, I see this tool likely to be used by people who participate in
the practice of p-hacking, whether deliberately or not. The ability to throw
lots of simple models quickly at lots of data mindlessly reporting some notion
of statistical significance is dangerous. I'm assuming your stats are not
(cannot) be adjusted in any fashion to implicate what you're really doing by
using an automated model-building/reporting regime in this way (potentially
running heaps of models on heaps of data until you find one that appears
'significant' based on a statistical test designed under the assumption that
this is NOT what you're doing). No where did i see any application of
train/test, sample/resample type methods to try to control for over-fitting in
the prediction application or truly estimate how predictive/replicable such a
technique would be in the real world.

While I appreciate the work done required to put something like this together
(a lot of it looks like a gui interface to my own exploratory
functions/scripts in R, for example), i genuinely believe this approach is
more dangerous/likely to lead to false conclusions than helpful.

~~~
incongruity
I agree, in this case, you’re right on (and I have another comment saying as
much) but _couldn’t_ there be a UI that _guides_ you safely through some of
those dangers? I have yet to see anything close to one but I could imagine a
system that would at least ask a few questions that would quickly disqualify a
dataset or intended analysis for some use cases. Imagine, if you will, turbo-
tax for (basic) statistical analyses.

As I said elsewhere, a simple interface doesn’t necessarily mean a correct
outcome - In short, most stats software is solving the wrong problem. Many
(especially this one) make it easy to get an answer, right or wrong. I’d
rather see them make it hard to get a wrong answer - or, perhaps, hard to get
an answer when you’re using it wrong.

~~~
ACow_Adonis
Hmmm. I understand that by answering in the negative (no, its not possible), i
would put myself into the "64k is enough for anybody" type comments. Which is
to say, since its not a logical impossibility and not a well defined concept
and our technology/understanding is increasing, odds are we'll at least make
headways towards it to the point that its already pretty good. One could argue
that we're already there compared to statistical environments of the 80's and
90's.

Honestly, I think this is a tricky human problem, not a tech problem.

My reasoning is thus. I've been known to argue that even R is bad from this
perspective: I view its success (apart from its free/OS nature) due to the
fact that it carries with it libraries, a functional flavour, tied around a
core engine/philosophy of implicit actions preference to result production
rather than bothering the user.

These enable a person (with just enough knowledge to be dangerous) to load an
externally authored package (that has neither been tested nor verified) with
one line, load a dataset with one line (which silently corrupted or changed
something during import), and apply a function in one line (which silently
coerced objects/values in the background and unreliably expressed/suppressed
errors and warnings). Where it does express warnings/errors, it does so
unreliably/unhelpfully, so amateurs are led down the path of excessive
warnings/errors where things continue on regardless: ignore them.

To many, what I've written up there is not a bad thing: you get statistical
analysis in three simple lines for free, all while copying and pasting scripts
from stack overflow or the internet.

Now, i'm actually working on my own hobby project of designing a
language/library for my own use which is designed around fixing those
principals: still function based, interactive, fast, no implicit coercion,
allowing flexibility while imposing restrains and guarantees.

But I'm under no illusion that it would necessarily be popular if i ever
realised it to the public. The attraction of R is that you get a model out in
three lines, rather than 14 errors and no result telling you that there are
issues involving realms of thought you didn't know you were ignorant in and
you'll have to go away and study before you continue, or even that your data
might not be suitable for what you're doing. It might not be a good piece of
work, but cynically, for the type of person buying into such a mind-set of
quick analysis via "darts thrown at an analytical wall", i'm not convinced
that quality genuinely matters to them (even though it matters in the effects
it has on the public further down the line).

And i've not even gotten into the problem that in the real world 90% of work
is not analysis/modelling but in data cleaning/munging, critical thinking and
technical problem solving, and that there's another layer of problems below
that one which most academics and professionals rarely engage in, which is
questioning the systematic/contextual nature of the data before it got to your
data set (which no software/interface i'm aware of currently addresses and
most people just blithely ignore).

------
stephen123
I video if it in action would be really helpful. Just reading the landing page
its hard to know how im supposed to use it. "Just click and explore" isnt very
convincing.

~~~
nxrabl
They link to a demo video near the bottom of the page:
[https://www.youtube.com/watch?v=IcA9YG9yJgs](https://www.youtube.com/watch?v=IcA9YG9yJgs)

------
devin
Since other comments on this thread have complained about missing screenshots.
Some can be found here: [https://itunes.apple.com/us/app/wizard-statistics-
analysis/i...](https://itunes.apple.com/us/app/wizard-statistics-
analysis/id495152161?mt=12)

------
csomar
There is a video link at the very bottom of the page. It'll take some hazard
to fall onto it. I'm not going to download a program and figure out how to use
it.

Why not have the video at the top. Maybe pop right on my face. Actually, these
are moments when I'd not mind a popup that takes focus out of a page.

------
abakker
SPSS user here, I run a bunch of surveys in Qualtrics and SurveyMonkey, and
frequently use their export to SPSS file functionality.

Often, I have questions that take the format of "for each of the following
categories please rank them between strongly disagree and Strongly agree". The
way these questions end up in the SPSS files are typically as different
variables for each row, and a 1,2,3,4, or 5 as the measurement along with the
labels.

Frequently, I want to pivot those types of questions by a variable like Region
or Number of Employees (categorical), and then see the resultant tables. This
is never fun, and inevitably takes a lot of time.

As others have said, statistics is a careful business that doesn't necessarily
warrant ease of access to all mathematical functions BUT, handling what SPSS
calls "Multiple Response Sets" better would be a godsend, just for the data
prep and visualization step. I still ultimately fall back on recoding these or
leveraging the MRS functional in SPSS to get this done (sometimes this is
better than just using pivot tables in excel).

It would be great to be able to specify this kind of thing in this program,
since without it, you can't really use/trust the computed percentages in some
question configurations. Take a real look at the SPSS Tables feature, the
Multiple Response Sets, and then visualization of them, and consider how that
data is actually coded in SPSS files (the common export of survey tools) and
maybe you can improve on that feature (It shouldn't be hard, MRS is a pretty
bad setup, but it gets the job done).

------
rounce
Just had a quick skim of the site and saw no screenshots just a load of
marketese. Next I head to the HN comments: some preach FUD, others are stauch
defenders. It seems very few speak from experience of actually using this
application. It seems a lot of the discussion stems from the poor marketing
than anything else.

------
vermooten
no screenshots?

~~~
anonfunction
Was thinking same thing, there is a link to a video at the bottom though.

~~~
fzil
and the video is blurry in 480p (maybe because it was uploaded 6 years ago?)

~~~
wenc
I came across this program about 6 years ago, and the webpage hasn't changed.
I have a suspicion that the program may not have been updated since, but it's
hard to tell.

~~~
devin
No, it has received frequent updates.

------
salmonz
The app should use mutually exclusive colors for the visualizations to
communicate the right and intended information.

------
trengrj
I'd recommend some screenshots or the video before you get to pricing.

Some of the graphics need to be improved. It would also be great to see why
this is better than tradition BI tools (Tableau etc) and what your unique
value proposition is.

------
mnky9800n
Is this close sourced? I'm not using a statistics package I don't trust or
that I can take apart to see what's wrong when it's returning weird results.

~~~
dman
How much are you willing to pay to use something like this? Would you still
pay if it was open source?

~~~
mnky9800n
I use python and R for all of my research. Why would I pay for anything when
those tools allow me to do these tasks for free?

------
tambourine_man
Please check your home page on 4” devices. Headline is clipped.

------
Nullabillity
> PS- Wizard is only available for Mac, but if you’re reading this on a PC,
> consider this: for the price of high-end statistics software, you can buy
> Wizard and still have enough money left over for a top-of-the-line MacBook
> Air or MacBook Pro. Amazing, isn’t it?

Wow, that's a great way to kill off any sympathy for him. Especially given
that he's apparently had 4-5 years to dig himself out of that hole.

~~~
crooked-v
It's not about "sympathy". It's about pointing out that similarly-targeted
apps like Analytica can cost $1000+ per license.

~~~
Nullabillity
$200 for this + $1000 for the cheapest macbook > your $1000 analytica license.
And that's before considering that you're now stuck lugging around an extra
paperweight everywhere, or that R is available for free.

~~~
goatlover
> or that R is available for free.

Along with Python and Julia.

