http://spssx-discussion.165.s1.nabble.com/SPSS-vs-R-tp5736226p5736235.html
I just found it now via Google, so don't know anything about it. But as the
> Thanks, Bruce!. I'll look at it.
> Subject: Re: SPSS vs R
>
> As some of you will know, there have been many articles and commentaries
> over
> the years decrying the use of Excel for serious statistical analysis.
> Here
> is a presentation that summarizes many of the issues.
>
>
>
http://biostat.mc.vanderbilt.edu/wiki/pub/Main/TheresaScott/StatsInExcel.TAScott.slides.pdf>
> For an introductory class where one wants to keep things relatively simple
> (and cheap), I would suggest using something like JASP instead.
>
>
https://jasp-stats.org/current-functionality/>
> HTH.
>
>
> bdates wrote
>> I'll weigh in briefly. I teach a grad course in research methods and
>> stats
>> in which I've used SPSS as a mandate of the program. Recently, the
>> program, recognizing that the likelihood of any of the students actually
>> doing research in the future was close to nil, has moved to the use of
>> Excel. That's good to the extent to which student's have more familiarity
>> with Excel and zero with SPSS; so they've not just been forced to learn
>> statistics and research methods, but a completely foreign software.
>>
>>
>> With that said, in preparation to move from using SPSS for assignments,
>> I'm exporting the datasets from SPSS to Excel and finding that the
>> structure of data in SPSS is not conducive to analysis in Excel.
>> Furthermore, Excel's structure seems clumsy. For example, to do an
>> independent samples t-test in Excel, entering the data ranges requires
>> that either two columns/variables be created - one for each group; or if
>> there is a group variable (e.g., treatment and control), the ranges
>> require that users copy first those values for one group into a range,
>> and
>> then for the other group into the second range. The likelihood for error
>> with all the copying and pasting is increased quite a bit.
>>
>>
>> Then there's the problem of completeness of analysis. The methods used in
>> either the basic correlational analysis or the Analysis Tool Pack gives
>> only the correlation, totally devoid of significance, intercept, standard
>> error, or confidence interval limits.
>>
>>
>> I'll use Excel because it represents a move the program has now mandated,
>> but with all the difficulty inherent in the lack of familiarity with
>> SPSS,
>> it probably is more intuitive tool for analysis in the long run.
>>
>>
>> Brian Dates
>> ________________________________
>> From: SPSSX(r) Discussion <
>
>> SPSSX-L@.UGA
>
>> > on behalf of Reka Solymosi <
>
>> reka.solymosi@.AC
>
>> >
>> Sent: Tuesday, June 12, 2018 5:59:39 AM
>> To:
>
>> SPSSX-L@.UGA
>
>> Subject: Re: SPSS vs R
>>
>>
>> Dear John,
>>
>>
>>
>> Thank you for all the detailed comments. While I never taught in SPSS (so
>> I cannot comment on that experience like Juanjo) I did receive all my
>> training in SPSS. It works in a university setting great, but once I left
>> academia, it was not very useful for me. Licences for SPSS are expensive,
>> and are *per PC* from what I remember. I worked at a local council as a
>> transport planning analyst, and then later as a crime analyst in London.
>> Neither were in well-funded places. I had access to Excel, and MapInfo. I
>> self-taught R and it was great not only because of it being free and
>> because of all the support and community around the open source ethos of
>> it, but because of the flexibility. There are an ever growing number of
>> packages available for R for free, which means that it can be used yes
>> for
>> graphics, but also for statistical modelling, for network analysis, for
>> text analysis, for data mining, as a GIS, to build interactive
>> dashboards,
>> to build presentations, and mostly for reproducible data manipulation
>> and
>> analysis. I have yet to find any other tool (other than maybe writing SQL
>> and more recently Python) that allows such a range in data querying,
>> manipulation and cleaning.
>>
>>
>>
>> That said, bringing it back to teaching in academia, I agree completely
>> with your suggestion that students need an introduction before throwing
>> them into R. I teach the first semester course (the one that students
>> take before moving on to the R based one) in Excel. I chose Excel over
>> SPSS simply due to the fact that no matter where they will go, there will
>> be Excel, even in the poorest local council. It gives enough of an
>> introduction to data analysis that they can then move on to R. So in that
>> sense we are following the suggestion you make, that they start with an
>> easier route to contingency tables via excel, and then move on to R.
>> Excel
>> can actually be a very powerful tool for data analysis if used right, and
>> also an accessible route in to interpreting, understanding, and examining
>> data.
>>
>>
>>
>> To be honest I think any way we can get students interested in data
>> analysis is good. I don’t hugely care if it’s SPSS, Excel, R, STATA, etc,
>> I think the most important is the core concept and getting students
>> interested in data analysis. I think we manage to achieve that here, we
>> even have a few of our graduating students this year applying for a
>> masters in data science, which coming from a criminology programme I
>> think
>> is somewhat unusual! But I also appreciate that we are standing on the
>> shoulders of giants in a way. I for one have made so much use of the work
>> and support from those like yourself with numerous years of experience in
>> teaching and researching the best ways for teaching quantitative methods.
>> I think there is a lot of very valuable material there, and I think that
>> it can be applied to any platform. I used many materials and resources
>> that showed examples in SPSS, and translated those to Excel or R.
>>
>>
>>
>> Ideally some resource for sharing platform agnostic resources could
>> actually be compiled and perhaps shared around? My material on using
>> Excel
>> is all available here:
https://maczokni.github.io/MSCD/ I know that last
>> summer I sent around quite a few requests for help to the quantitative
>> methods teaching list, and I would be happy if I could pay back somehow.
>> Maybe some central open-source repository of training material that can
>> be
>> applied by any one to any platform they choose to use, but that is based
>> on all the work everyone is doing, to bring us all together?
>>
>>
>>
>> Let me know any thoughts!
>>
>>
>>
>> Many thanks,
>> Reka
>>
>>
>>
>> From: John F Hall [mailto:
>
>> johnfhall@
>
>> ]
>> Sent: 12 June 2018 10:24
>> To:
>
>> SPSSX-L@.UGA
>
>> Cc: Juan Medina-Ariza; Reka Solymosi
>> Subject: SPSS vs R
>>
>>
>>
>> As part of the ESRC-Nuffield Q-step initiative
>> (
http://www.nuffieldfoundation.org/q-step) to improve quantitative
>> methods
>> teaching in undergraduate social science degrees in the UK, a new
>> one-semester quantitative criminology course is being taught to
>> undergraduates at Manchester using R, mainly because of its graphic
>> capabilities.
>>
>> See
http://jjmedinaariza.github.io/R-for-Criminologists/ for full course
>> notes.
>>
>>
>>
>> In the accompanying pedagogical rationale Professor Juanjo Medina
>> explains
>> why (although he admits that R has problems with crosstabs at which SPSS
>> is excellent.)
>>
>>
>>
>> It is simple. I was sick to the bone of teaching with SPSS. Why should I
>> bother to be a publicist for IBM? . . .But I never quite fell in love
>> with
>> SPSS, its ugly graphic system, its patched up inconsistent menu design,
>> etc. Its whole architecture, easy in the eye for casual users, seem
>> designed to encourage bad habits among future analysts. In the meantime I
>> continue using a variety of tools for my own research (STATA, MPlus, etc)
>> until I met R and fell in love with it.
>>
>> See
>>
https://rawgit.com/jjmedinaariza/LAWS70821/master/rcommander.html#motivation>>
>>
>>
>> As someone who had to teach and assess Data Management and Analysis (at
>> both undergraduate and postgraduate level) within a tight 13-week
>> semester
>> I still feel that SPSS is an easier, and better, route to Quantitative
>> Methods (via contingency tables rather than multivariate statistics)
>> perhaps leading to R at a later stage.
>>
>>
>>
>> John F Hall MA (Cantab) Dip Ed (Dunelm)
>>
>> [Retired academic survey researcher]
>>
>>
>>
>> Email:
>
>> johnfhall@
>
>> <mailto:
>
>> johnfhall@
>
>> >
>>
>> Website: Journeys in Survey
>> Research<
http://surveyresearch.weebly.com/>>>
>> Course: Survey Analysis Workshop
>> (SPSS)<
http://surveyresearch.weebly.com/1-survey-analysis-workshop-spss.html>>>
>> Research: Subjective Social Indicators (Quality of
>> Life)<
http://surveyresearch.weebly.com/3-subjective-social-indicators-quality-of-life.html>>>
>>
>>
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> -----
> --
> Bruce Weaver
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