As part of the ESRCNuffield Qstep initiative (http://www.nuffieldfoundation.org/qstep) to improve quantitative methods teaching in undergraduate social science degrees in the UK, a new onesemester quantitative criminology course is being taught to undergraduates at Manchester using R, mainly because of its graphic capabilities. See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week 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: [hidden email] Website: Journeys in Survey Research Course: Survey Analysis Workshop (SPSS) Research: Subjective Social Indicators (Quality of Life) 
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 wellfunded
places. I had access to Excel, and MapInfo. I selftaught 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
opensource 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, From: John F
Hall [mailto:[hidden email]] As part of the ESRCNuffield Qstep initiative (http://www.nuffieldfoundation.org/qstep) to improve quantitative methods
teaching in undergraduate social science degrees in the UK, a new onesemester quantitative criminology course is being taught to undergraduates at Manchester using R, mainly because of its graphic capabilities.
See
http://jjmedinaariza.github.io/RforCriminologists/ 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 13week 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:
[hidden email] Website:
Journeys in Survey Research Course:
Survey Analysis Workshop (SPSS) Research:
Subjective Social Indicators (Quality of Life) 
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 ttest 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 <[hidden email]> on behalf of Reka Solymosi <[hidden email]>
Sent: Tuesday, June 12, 2018 5:59:39 AM To: [hidden email] 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 wellfunded places. I had access to Excel, and MapInfo. I selftaught 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 opensource 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,
From: John F Hall [mailto:[hidden email]]
As part of the ESRCNuffield Qstep initiative (http://www.nuffieldfoundation.org/qstep) to improve quantitative methods teaching in undergraduate social science degrees in the UK, a new onesemester quantitative criminology course is being taught to undergraduates at Manchester using R, mainly because of its graphic capabilities. See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week 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: [hidden email] Website: Journeys in Survey Research Course: Survey Analysis Workshop (SPSS) Research: Subjective Social Indicators (Quality of Life)

A couple of comments on Brian's Post: (1) I currently teach statistics to psych majors and I use both Excel and SPSS. I use a common data set (consisting of participant background, performance on one unexpected memory (Exp 1 level betweensubjects design) and a second expected memory experiment (Exp 2 3 level withinsubject design). I use an independent groups ttest for Experiment 1 (plus test for variance and ttest for unequal variance regardless of the F for variances) and a oneway Repeated Measures ANOVA (2way ANOVA without replication or ANOVA by blocks  subjects as block  see Glass & Hopkins 1st edition Fig 1906 and G&H 3ed Fig 2001 for ANOVA layout, calculations, structural model [1st ed; 2nd Ed relies on Excel output]. We do analyses in both Excel & SPSS so folks can see how (a) getting the analysis differ in the two, (2) some things are easier in Excel while others are easier in SPSS, and (3) the Repeated Measures ANOVA output is much easier to understand in Excel than in SPSS and I show how to do the calculations for the Fisher's LSD post hoc test and the Bonferroni corrected ttest  one would have to do this for either Excel or SPSS because for some reason SPSS does not provide the actual critical LSD or Bonferroni minimum difference. More shortly. (2) Although I tell my students that they will have access to Excel anywhere they are (unless we have a Zombie apocalyse, in which make sure you have a good hand calculator and lots or ammo) they should really upon Excel 2016 and not earlier versions. There have been some changes in the "keywords" for use in the formulas (which one can use instead of the toolpak  Mac SPSS before 2016 did not provide the toolpak but now both are standardized starting from 2016)  compare Excel 2007 with 2013 and later versions. More importantly, a number of calculations are prone to error in earlier version though mostly for more complex calculations. Bruce McCullough and others have documented some of these problems, starting with Excel 2007 to more recent versions (Excel 2016 appears to be completely overhauled and I *think* many problmes have been corrected); one example of this work is the following:
McCullough, Bruce D., and David A. Heiser. "On the accuracy of statistical procedures in Microsoft Excel 2007." Computational Statistics & Data Analysis 52.10 (2008): 45704578.
One should not assume that Excel from different years will produce the same results. (3) It should come as no surprise that because of the problem encountered in (2) above, enterprising statistical programs have created more accurate addons for Excel that provide not only more accurate results but also new procedures and additional analyses (I have looked at XLStat because some folks at NYU use it but it also suffers from the problem of being too expensive). So, one can use Excel in combination with SPSS (as well as pointing out that any really, really important analysis should be conducted by two different programs that approach the analysis differently), either with toolpak or the tedious old fashion layouts that are still common in many undergrad statistics texts. Or one can point out that the independent groups ttest can be gotten by putting the following equation in a cell t = (M1  M2)/sqrt(VE1 + VE2) where M = Mean and VE = Variance Error (there is a formula for this; one can point out that is known as the "separate variance ttest" and in the form presented, N1 = N2; by dividing sample variance 1 by N1 and sample variance 2 by N2 which is the old school of calculating t when the variances are difference  see Welch for how to calculate the appropriate degress of freedom). Indeed, using the formulas provided by Excel simplifies at number of the computations that, if done by hand, are timeconsuming and prone to error. Mike Palij New York University On Thu, Jun 14, 2018 at 3:02 PM, Dates, Brian <[hidden email]> wrote:

Administrator

In reply to this post by bdates
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://jaspstats.org/currentfunctionality/ 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 ttest 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 < > SPSSXL@.UGA > > on behalf of Reka Solymosi < > reka.solymosi@.AC > > > Sent: Tuesday, June 12, 2018 5:59:39 AM > To: > SPSSXL@.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 wellfunded places. I had access to Excel, and MapInfo. I > selftaught 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 opensource 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: > SPSSXL@.UGA > Cc: Juan MedinaAriza; Reka Solymosi > Subject: SPSS vs R > > > > As part of the ESRCNuffield Qstep initiative > (http://www.nuffieldfoundation.org/qstep) to improve quantitative methods > teaching in undergraduate social science degrees in the UK, a new > onesemester quantitative criminology course is being taught to > undergraduates at Manchester using R, mainly because of its graphic > capabilities. > > See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week 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/1surveyanalysisworkshopspss.html> > > Research: Subjective Social Indicators (Quality of > Life)<http://surveyresearch.weebly.com/3subjectivesocialindicatorsqualityoflife.html> > > > > ===================== To manage your subscription to SPSSXL, send a > message to > LISTSERV@.UGA > <mailto: > LISTSERV@.UGA > > (not to SPSSXL), with no body text except the command. To leave the > list, send the command SIGNOFF SPSSXL For a list of commands to manage > subscriptions, send the command INFO REFCARD > > ===================== > To manage your subscription to SPSSXL, send a message to > LISTSERV@.UGA > (not to SPSSXL), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSXL > For a list of commands to manage subscriptions, send the command > INFO REFCARD   Bruce Weaver [hidden email] http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above.  Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD

Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above. 
Thanks, Bruce!. I'll look at it.
Brian
From: SPSSX(r) Discussion <[hidden email]> on behalf of Bruce Weaver <[hidden email]>
Sent: Thursday, June 14, 2018 4:08:25 PM To: [hidden email] 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://jaspstats.org/currentfunctionality/ 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 ttest 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 < > SPSSXL@.UGA > > on behalf of Reka Solymosi < > reka.solymosi@.AC > > > Sent: Tuesday, June 12, 2018 5:59:39 AM > To: > SPSSXL@.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 wellfunded places. I had access to Excel, and MapInfo. I > selftaught 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 opensource 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: > SPSSXL@.UGA > Cc: Juan MedinaAriza; Reka Solymosi > Subject: SPSS vs R > > > > As part of the ESRCNuffield Qstep initiative > (http://www.nuffieldfoundation.org/qstep) to improve quantitative methods > teaching in undergraduate social science degrees in the UK, a new > onesemester quantitative criminology course is being taught to > undergraduates at Manchester using R, mainly because of its graphic > capabilities. > > See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week 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/1surveyanalysisworkshopspss.html> > > Research: Subjective Social Indicators (Quality of > Life)<http://surveyresearch.weebly.com/3subjectivesocialindicatorsqualityoflife.html> > > > > ===================== To manage your subscription to SPSSXL, send a > message to > LISTSERV@.UGA > <mailto: > LISTSERV@.UGA > > (not to SPSSXL), with no body text except the command. To leave the > list, send the command SIGNOFF SPSSXL For a list of commands to manage > subscriptions, send the command INFO REFCARD > > ===================== > To manage your subscription to SPSSXL, send a message to > LISTSERV@.UGA > (not to SPSSXL), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSXL > For a list of commands to manage subscriptions, send the command > INFO REFCARD   Bruce Weaver [hidden email] http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above.  Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD 
Administrator

Here's another one to check out, Brian:
https://www.jamovi.org/ I just found it now via Google, so don't know anything about it. But as the webpage says, it is "built on top of the R statistical language, giving you access to the best the statistics community has to offer." And apparently, it can generate the R code too. bdates wrote > Thanks, Bruce!. I'll look at it. > > > Brian > ________________________________ > From: SPSSX(r) Discussion < > SPSSXL@.UGA > > on behalf of Bruce Weaver < > bruce.weaver@ > > > Sent: Thursday, June 14, 2018 4:08:25 PM > To: > SPSSXL@.UGA > 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://jaspstats.org/currentfunctionality/ > > 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 ttest 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 < > >> SPSSXL@.UGA > >> > on behalf of Reka Solymosi < > >> reka.solymosi@.AC > >> > >> Sent: Tuesday, June 12, 2018 5:59:39 AM >> To: > >> SPSSXL@.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 wellfunded places. I had access to Excel, and MapInfo. I >> selftaught 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 opensource 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: > >> SPSSXL@.UGA > >> Cc: Juan MedinaAriza; Reka Solymosi >> Subject: SPSS vs R >> >> >> >> As part of the ESRCNuffield Qstep initiative >> (http://www.nuffieldfoundation.org/qstep) to improve quantitative >> methods >> teaching in undergraduate social science degrees in the UK, a new >> onesemester quantitative criminology course is being taught to >> undergraduates at Manchester using R, mainly because of its graphic >> capabilities. >> >> See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week >> 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/1surveyanalysisworkshopspss.html> >> >> Research: Subjective Social Indicators (Quality of >> Life)<http://surveyresearch.weebly.com/3subjectivesocialindicatorsqualityoflife.html> >> >> >> >> ===================== To manage your subscription to SPSSXL, send a >> message to > >> LISTSERV@.UGA > >> <mailto: > >> LISTSERV@.UGA > >> > (not to SPSSXL), with no body text except the command. To leave the >> list, send the command SIGNOFF SPSSXL For a list of commands to manage >> subscriptions, send the command INFO REFCARD >> >> ===================== >> To manage your subscription to SPSSXL, send a message to > >> LISTSERV@.UGA > >> (not to SPSSXL), with no body text except the >> command. To leave the list, send the command >> SIGNOFF SPSSXL >> For a list of commands to manage subscriptions, send the command >> INFO REFCARD > > > > > >  >  > Bruce Weaver > bweaver@ > http://sites.google.com/a/lakeheadu.ca/bweaver/ > > "When all else fails, RTFM." > > NOTE: My Hotmail account is not monitored regularly. > To send me an email, please use the address shown above. > >  > Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ > > ===================== > To manage your subscription to SPSSXL, send a message to > LISTSERV@.UGA > (not to SPSSXL), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSXL > For a list of commands to manage subscriptions, send the command > INFO REFCARD > > > ===================== > To manage your subscription to SPSSXL, send a message to > LISTSERV@.UGA > (not to SPSSXL), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSXL > For a list of commands to manage subscriptions, send the command > INFO REFCARD   Bruce Weaver [hidden email] http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above.  Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD

Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above. 
Administrator

Here's a little more info on JASP & jamovi.
"Jamovi is made by developers who used to work on JASP, and you’ll see JASP and jamovi look and feel very similar. I’d recommend downloading and installing both these excellent free software packages. Where JASP aims to provide Bayesian statistical methods in an accessible and userfriendly way (and you can do all sorts of Bayesian analyses in JASP), the core aim of jamovi is wanting to make software that is ‘“community driven”, where anyone can develop and publish analyses, and make them available to a wide audience’. This means that if I develop statistical analyses, such as equivalence tests, I can make these available through jamovi for anyone who wants to use these tests. I think that’s really cool, and I’m super excited my equivalence testing package TOSTER is now available as a jamovi module." Source: http://daniellakens.blogspot.com/2017/03/equivalencetestinginjamovi.html Bruce Weaver wrote > Here's another one to check out, Brian: > > https://www.jamovi.org/ > > I just found it now via Google, so don't know anything about it. But as > the > webpage says, it is "built on top of the R statistical language, giving > you > access to the best the statistics community has to offer." And > apparently, > it can generate the R code too. > > > > > bdates wrote >> Thanks, Bruce!. I'll look at it. >> >> >> Brian >> ________________________________ >> From: SPSSX(r) Discussion < > >> SPSSXL@.UGA > >> > on behalf of Bruce Weaver < > >> bruce.weaver@ > >> > >> Sent: Thursday, June 14, 2018 4:08:25 PM >> To: > >> SPSSXL@.UGA > >> 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://jaspstats.org/currentfunctionality/ >> >> 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 ttest 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 < >> >>> SPSSXL@.UGA >> >>> > on behalf of Reka Solymosi < >> >>> reka.solymosi@.AC >> >>> > >>> Sent: Tuesday, June 12, 2018 5:59:39 AM >>> To: >> >>> SPSSXL@.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 wellfunded places. I had access to Excel, and MapInfo. >>> I >>> selftaught 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 opensource 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: >> >>> SPSSXL@.UGA >> >>> Cc: Juan MedinaAriza; Reka Solymosi >>> Subject: SPSS vs R >>> >>> >>> >>> As part of the ESRCNuffield Qstep initiative >>> (http://www.nuffieldfoundation.org/qstep) to improve quantitative >>> methods >>> teaching in undergraduate social science degrees in the UK, a new >>> onesemester quantitative criminology course is being taught to >>> undergraduates at Manchester using R, mainly because of its graphic >>> capabilities. >>> >>> See http://jjmedinaariza.github.io/RforCriminologists/ 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 13week >>> 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/1surveyanalysisworkshopspss.html> >>> >>> Research: Subjective Social Indicators (Quality of >>> Life)<http://surveyresearch.weebly.com/3subjectivesocialindicatorsqualityoflife.html> >>> >>> >>> >>> ===================== To manage your subscription to SPSSXL, send a >>> message to >> >>> LISTSERV@.UGA >> >>> <mailto: >> >>> LISTSERV@.UGA >> >>> > (not to SPSSXL), with no body text except the command. To leave >>> the >>> list, send the command SIGNOFF SPSSXL For a list of commands to manage >>> subscriptions, send the command INFO REFCARD >>> >>> ===================== >>> To manage your subscription to SPSSXL, send a message to >> >>> LISTSERV@.UGA >> >>> (not to SPSSXL), with no body text except the >>> command. To leave the list, send the command >>> SIGNOFF SPSSXL >>> For a list of commands to manage subscriptions, send the command >>> INFO REFCARD >> >> >> >> >> >>  >>  >> Bruce Weaver > >> bweaver@ > >> http://sites.google.com/a/lakeheadu.ca/bweaver/ >> >> "When all else fails, RTFM." >> >> NOTE: My Hotmail account is not monitored regularly. >> To send me an email, please use the address shown above. >> >>  >> Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ >> >> ===================== >> To manage your subscription to SPSSXL, send a message to > >> LISTSERV@.UGA > >> (not to SPSSXL), with no body text except the >> command. To leave the list, send the command >> SIGNOFF SPSSXL >> For a list of commands to manage subscriptions, send the command >> INFO REFCARD >> >> >> ===================== >> To manage your subscription to SPSSXL, send a message to > >> LISTSERV@.UGA > >> (not to SPSSXL), with no body text except the >> command. To leave the list, send the command >> SIGNOFF SPSSXL >> For a list of commands to manage subscriptions, send the command >> INFO REFCARD > > > > > >  >  > Bruce Weaver > bweaver@ > http://sites.google.com/a/lakeheadu.ca/bweaver/ > > "When all else fails, RTFM." > > NOTE: My Hotmail account is not monitored regularly. > To send me an email, please use the address shown above. > >  > Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ > > ===================== > To manage your subscription to SPSSXL, send a message to > LISTSERV@.UGA > (not to SPSSXL), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSXL > For a list of commands to manage subscriptions, send the command > INFO REFCARD   Bruce Weaver [hidden email] http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above.  Sent from: http://spssxdiscussion.1045642.n5.nabble.com/ ===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD

Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." NOTE: My Hotmail account is not monitored regularly. To send me an email, please use the address shown above. 
In reply to this post by bdates
I have encountered programs where SPSS have been abandoned in favor of Excel. And the teachers seem to end up with a messy set of functions and
use of Analysis Toolpak, which for the students usually makes the courses a matter of dealing with Excel technicalities. Frustrating, and as for the ambition to make students learn about research methods, it is not a sound way to do so. My advice has always been to reconsider the use of Excel, with the added comment that if they have to stick with Excel they would probably do much
better by using Excel for the summary measures you can build with “Pivot Tables” in Excel followed by use of web sites such as openepi.com. Most of the Excel function could and should be avoided. My experience is that this gives students the chance to work
with statistics rather than with Excel. Robert
Robert Lundqvist

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