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Jamovi vs JASP
Feb 4, 2025
Comparing two free statistics software packages, Jamovi and JASP, for ease of use, features, and usability in some common tests
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0:00
so hi my name is Dave uh I'm going to
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guide you through this little tour of
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jamovi and jasp where we compare the two
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of them it's pretty quick skip any part
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that you don't feel is important to you
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or is necessary my background is mostly
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in organizational change and
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organizational research but I also teach
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statistics as part of other courses so
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let's get
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started so here we are and you can see
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that there are some things in Gray these
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are the things that the SPSS file we
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imported already had labeled as missing
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values you can make everything bigger or
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smaller you can change the color palette
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and such which is nice and you can add
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new modules which is nice so you see
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these are modules that are already here
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and then there's other ones that we can
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add in these are bundled so we can go
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out to the library and we can add a few
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things so for example we can add an
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Editor to run R code inside Jovi which
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then gives you syntax let's just get out
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of here and go back in it is really nice
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to have the missing values here in the
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data editor showing up as gray SPSS
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doesn't do that at least the versions
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I've used don't and in fact it's the
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first time I've ever seen it like this
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now if you want to see which values are
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designated as missing you double click
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on the variable name and here is the
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variable description or variable label
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as SPSS calls it and that's that's
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imported directly from SPSS of course
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you can set it here or change it here
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yourself if you want to along with what
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kind of measurement it is so this is
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nominal which means that the numbers
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aren't really
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numbers and that makes sense because
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it's basically a yes or no question here
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uh should people be able to use health
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insurance for abortion yes or no and
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then you've got three things that are
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labeled is missing as you see here 0 8
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and N 0 is inapplicable eight is don't
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know nine is no answer so these are all
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uh missing values and you can click on
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any of these once you've double clicked
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in here and you see the same results
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let's take a look now at uh transforming
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and recoding basically recoding is here
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under transform you might notice by the
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way I should point out that it's showing
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you value labels so the actual values
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here are own numbers right now where it
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says people should be able let's see
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people should not be able is what it
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says so that would actually be the
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number two here so let's take a look at
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this one here do you have a moral abort
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uh a moral opposition to abortion if you
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take a look then you find that uh one is
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opposed two is not opposed three is it
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depends normally we would want it to go
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1 32 basically because we'd want it
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depends to be in the middle so if you're
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opposed you're on one side if you're not
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opposed you're on the other and if you
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say it depends you're in the middle so
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really we have to swap this two and this
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three well how do we do that is we
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transform so how do we take this one and
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three and swap them is we can either
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compute a new variable with everything
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set up correctly that turns out not to
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actually work very well here or we
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transform and we say that we will use a
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new
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transformation and so we add a recode
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condition that if the source equals
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notice the two equal signs two then we
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use three we add a condition if it
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equals three we use two now in SPSS if
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you did this you would run into trouble
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because it would convert all the twos to
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threes and then all the threes including
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the ones that used to be twos would go
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to two but here you will notice here it
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will actually work properly oh let's
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also do a Source equals 1 we'll
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basically copy those over and else we
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will use zero we'll call it uh
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swap two and
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three and we will say that the
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description is just
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recoded to Three
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swap and the suffix will be
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fixed and uh we'll go back up and now we
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should see that it is is fixed now of
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course it's just showing the numbers now
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if you take a look then you see that
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where it says morally opposed it's one
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just says it was where it says it
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depends it's now two let's move this
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over and not morally opposed is three so
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it's now I apologize for doing the most
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complicated thing nearly
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first but recoding is of in handy so
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let's say that we take a look at the
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people who want to pay for abortion with
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insurance or not and we will see how
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they feel about abortion being moral
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you'll notice that as I put things in
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it's
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already taking a look at the T tests
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again grouping variable it has to be uh
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one a binary variable a dichotomus
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variable one where there's only two
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possible values or else this will not
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work you can't say like you can in SPSS
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or pspp I'm going to put in this
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variable of age groups and compare the
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youngest and the oldest by specifying
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that I'm going to to compare say groups
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one with group four won't work uh I can
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show you by will put AB moral in here
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and it says must have exactly two levels
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uh so here we see that there is a
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violation of the Assumption of equal
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variances SPSS will give you two sets of
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results one where it assumes equal
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variances and one where it doesn't here
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you have to know to click on Welches or
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man Whitney depending on the situation
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I'm going to stick with Welches and you
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see it's the same P value it's even the
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same statistic different degrees of
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freedom and you're not violating any uh
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rules I always like to see the
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descriptives so I can compare the means
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by I and here they are do a quick look
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at regressions so we'll do a linear
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regression we'll try to predict uh
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opposition or lack of opposition to
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abortion with let's see adults in the
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household age well that's an interesting
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uh error that I've never seen so let's
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take adults out and we'll just do age
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let's see what cohort they're
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in that's absolutely fascinating because
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it was not doing this before when I was
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testing it but it doesn't seem to be
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giving me let's try
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income all right it seems to like these
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we'll just do age and income you might
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notice that uh we don't have a choice of
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what type of analysis to do it does
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enter and only enter so let's do it with
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two models we'll assume that age is the
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most important and we'll add a new block
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and we'll drag income in there and now
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we see that we've got our two models it
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doesn't label our two models which would
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be nice but it does tell us that we can
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explain about what is that 6% of
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attitude towards abortion with age and
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then another 0.1% or so with both age
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and income and we can add in all sorts
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of things like assumption checks of
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various types uh we can check the
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adjusted R squar and we can look at some
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other things as well we can do the Inova
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so it's basically most of what you get
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with SPSS but in a somewhat different
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way usually I've never seen an error
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message in this before so it might be
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something with this data set or it might
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be a bug in the program now what about
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copying the results to word you might
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ask
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well let's find out what that's
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like copy
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table and you see it pastes in as an
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unnecessarily complicated table it's
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still nice to do it this way because
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when you do a correlation table it'll
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come out quite
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[Music]
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nicely as you saw you can add in modules
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and one of the libraries you can add in
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lets you run our code it does run on R
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and uh once that's
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there if you know R code you can run it
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I don't see any journaling which would
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be nice and it would be very convenient
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if the r code could be set up to print
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out along with the analyses especially
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if you're a faculty member trying to
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figure out what your students were doing
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but I don't see any way of doing that
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there might be a way but I don't see it
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so let's move on to jasp
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[Music]
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so here we are in jasp and I've just
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uploaded the exact same file and you
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might have noticed a couple of
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differences one big difference is that
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instead of having missing values grade
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out they're completely blank again these
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are all actually numbers in these
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columns but it's showing you the value
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labels so we can double click here we
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get a very similar uh report where we
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can put in custom values for the missing
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values right now again missing values
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are blank and it did that automatically
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which you may or may not want usually I
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have to admit I really don't care
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because I don't you know they're missing
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values I generally just leave them out
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occasionally I find something else that
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I want to make missing or if I'm
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importing from Excel or tab delimited
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format or something like that then I'll
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want to set missing values myself so
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let's take a quick look at recoding if
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we can do that so let's try I go here to
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data editing mode and you really don't
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seem to be able to change data and
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compute things you can compute with our
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code uh and this is where I give up and
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I say maybe you should do your recoding
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somewhere else because this looks like
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it's going to be incredibly hard to
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do you might notice that there's now
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basy in here to confuse your students as
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well as classical uh let's go to
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dependent samples we'll do the same
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thing we did before grouping variable do
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you think Insurance should be able to
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pay now the problem here of course is
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that if we use the morality of abortion
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which is right here then we get
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something that is probably accurate but
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makes no sense so let's take a look at
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age and we'll see what happens and again
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as I put things in and out of these
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windows the results come up instantly
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both these program s are astoundingly
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fast and there's no violation of the
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that the variances are similar for both
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groups so you don't get an error but if
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we wanted to we could get the Welch test
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just like that now let's go to
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regression we'll do the same thing that
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we did before we'll try to predict uh
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let's see it's hard to predict morality
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really we're going
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to uh but it will be completely
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meaningless because of the way it's
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coded just remember that
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so let's look at age and what else do we
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look at before income there's income
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16 and you see it immediately pops up on
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the right it is absurdly fast let's try
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something that might be more there we go
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now we get two models you don't want to
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use these methods in reality uh we're
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just playing around right now I do have
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other data sets that would be more
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appropriate for this where I actually
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know all the variables quite well here
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we have an R squ of just about zero and
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another one
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of uh 2% which is really pretty small
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trying to predict age using income and
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ab from memory you notice the
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description didn't come through it did
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not import any of the
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SPSS Variable labels which is a real
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problem if you're importing SPSS files
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it's not a real problem if you're
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creating your own data files it's quite
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nice really uh how fast this is and how
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nicely form formed these results are it
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gives you the Innova by default you can
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shut that off if you want to or you can
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add other things in as you see it's very
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similar you can have the r squar change
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I always think that should be in there
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by default can add in descriptive so
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that you can see how many people are in
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each group and what the averages are
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also handy to make sure you're not
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making mistakes we have to uh copy and
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paste to word so let's do
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that and you see it's almost exactly the
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same a lot of the underlying code for
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jamovi and jasp is probably the same I
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suspect that they are branches of the
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same project and as time has go gone on
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they've diverged more and more and more
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they both use R
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underneath and the sad thing is that
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jasp is really although it's very very
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fast and it's very convenient it also
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takes up over two gigabytes of disk
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space whereas Jovi only uses about let's
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find out for sure there's this very nice
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site code Mac stats. org where I write
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down things that I've learned so here it
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is under
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free stats and you can see that I
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compared these here we go so the
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download for jasp is 1.3 gabt and for
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jamovi it's 415
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megabytes when they're on the
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disc jasp ISS 2.2 GB and jamovi is 940
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megabytes now one other nice thing is we
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were talking about syntax and journaling
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so your R console gives you the uh
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syntax and here it is now so you can
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type in R code and you might be
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able to save things in an editor so
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these are the standard missing values
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across your entire data set you can
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change these if you want to uh you can
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use a spreadsheet Editor to do your
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recoding that's their way around any
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problems with Cod
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you can change through you have more
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control over the what the results look
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like including showing the r syntax when
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you do things and that both helps you to
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learn and it helps you if you're having
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your students do things then you know
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what variables they were using very
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easily and you can see exactly what they
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were doing so here you see it happened
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retroactively so if we want to do this T
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Test in the console we can just paste it
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right here in theory
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ah okay and that is my summary these are
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both very very good programs it's
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amazing what you get for free and they
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are somewhat different once you get
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inside but the basic techniques are very
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very similar from one to the other I
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expect them to keep on diverging in some
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ways and also to keep on getting better
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but you see that it's been doing this
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rather instantly and this data set here
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is not small it's got over 2,000 uh
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cases in it and an awful lot of
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variables I go through and there's
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hundreds of variables in this
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thing so I wish you luck with your