I participate peripherally on a listserve for middle- and high-school
science teachers. Sometimes questions about graphing or data analysis come up. I never miss an opportunity to advocate for R. However, the teachers are often skeptical that their students would be able to issue commands or write a little code; they think it would be too difficult. Perhaps this stems from the Microsoft- and spreadsheet-centered, pointy-clicky culture prevalent in most US public schools. Then again, I have little experience teaching this age group, besides my own kids and my Science Olympiad team, so I respect their concerns and expertise. I don't know yet what software they generally use, but I suspect MS Excel and SPSS. Now I have to put my money where my mouth is. I've offered to visit a high school and introduce R to some fairly advanced students participating in a longitudinal 3-year science research class. I anticipate keeping things very simple: --objects and the fact that there is stuff inside them. str(), head(), tail() --how to get data into R --dataframes, as I imagine they will mostly be using single, "rectangular" datasets --a lot of graphics (I can't imagine that plot(force, acceleration) is beyond a high-schooler's capability.) --simple descriptive statistics --maybe t-tests, chi-square tests, and simple linear regression. Alas, probably more than we would have time to cover. Has anyone done anything with R in high schools? Thanks. --Chris Ryan SUNY Upstate Medical University Binghamton Clinical Campus ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In addition to whatever feedback you may get here, you might subscribe
to the SIG-Teaching list for another interested population. Michael On Tue, Apr 17, 2012 at 10:46 PM, Christopher W Ryan <[hidden email]> wrote: > I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. > > Alas, probably more than we would have time to cover. > > Has anyone done anything with R in high schools? > > Thanks. > > --Chris Ryan > SUNY Upstate Medical University > Binghamton Clinical Campus > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
Hi Chris,
I am not sure, whether introducing R to High School students would be a good idea as I feel we should encourage students to sketch the graphs in paper to get their concepts right. Excel is fine, but - if I write an equation on the board, will the student be able to visualize its graph? Allowing students to use software to plot graphs at a very early age may hinder that learning. What I would focus on (as the teacher pointed out - that they may not be able to write code) - is being able to write simple codes to get a grasp on programming (they can use QBASIC which is one of the simplest programming softwares). R to my mind should be introduced at an undergraduate level - where they are able to use its real power (vectors, matrices, graphics etc.). Thats my view :) Regards, Indrajit ________________________________ From: Christopher W Ryan <[hidden email]> To: R-help <[hidden email]> Sent: Wednesday, April 18, 2012 8:16 AM Subject: [R] introducing R to high school students I participate peripherally on a listserve for middle- and high-school science teachers. Sometimes questions about graphing or data analysis come up. I never miss an opportunity to advocate for R. However, the teachers are often skeptical that their students would be able to issue commands or write a little code; they think it would be too difficult. Perhaps this stems from the Microsoft- and spreadsheet-centered, pointy-clicky culture prevalent in most US public schools. Then again, I have little experience teaching this age group, besides my own kids and my Science Olympiad team, so I respect their concerns and expertise. I don't know yet what software they generally use, but I suspect MS Excel and SPSS. Now I have to put my money where my mouth is. I've offered to visit a high school and introduce R to some fairly advanced students participating in a longitudinal 3-year science research class. I anticipate keeping things very simple: --objects and the fact that there is stuff inside them. str(), head(), tail() --how to get data into R --dataframes, as I imagine they will mostly be using single, "rectangular" datasets --a lot of graphics (I can't imagine that plot(force, acceleration) is beyond a high-schooler's capability.) --simple descriptive statistics --maybe t-tests, chi-square tests, and simple linear regression. Alas, probably more than we would have time to cover. Has anyone done anything with R in high schools? Thanks. --Chris Ryan SUNY Upstate Medical University Binghamton Clinical Campus ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
Christopher,
I suggest that you look at R through Excel. This is a Springer book that Erich Neuwirth and I wrote. It is designed as a computational supplement to any introductory Statistics book. It uses Erich's RExcel to give either menu access to R from Excel (using Rcmdr embedded into the Excel menu system), or by placing any R function inside the Excel automatic recalculation model. RExcel is available either in the RExcelInstaller package from CRAN, or fully integrated into a complete R system from rcom.univie.ac.at. Go to the Downloads page and download the current RAndFriends installer. We have discussions on using RExcel in the classroom in the Literature and presentations section on the Wiki page at the rcom site. Several of the links are to papers at the UseR! conferences. This one specifically addresses teaching: http://www.r-project.org/useR-2006/Slides/BaierEtAl.pdf Baier, T., Heiberger, R., Neuwirth, E., Schinagl, K., Grossmann, W. (2007). Using R for teaching statistics to nonmajors: Comparing experiences of two different approaches. Paper presented at the UseR 2006, Vienna. Rich On Apr 17, 2012, at 22:46, Christopher W Ryan <[hidden email]> wrote: > I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. > > Alas, probably more than we would have time to cover. > > Has anyone done anything with R in high schools? > > Thanks. > > --Chris Ryan > SUNY Upstate Medical University > Binghamton Clinical Campus > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
On Tue, Apr 17, 2012 at 10:46 PM, Christopher W Ryan
<[hidden email]> wrote: > I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. > I have some experience in this and would have to agree with Indrajit that this is not a good idea. When I tried to teach R to a high school student it was not very successful. Certainly based on that experience the list above is way too complex. Don't teach anything on that list at all. The number of concepts involved in that is simply overwhelming. Also avoid teaching anything that requires complex installation if you want them to be able to carry it forward by themselves. I would expect the reaction would be that most will have no interest and the ones that do will be frustrated by the large number of concepts needed to get going. The only part that seemed to trigger any interest was when I showed the large list of colors available in colors() and then playing with inserting different colors in: colors() plot(1:5, col = "violetred") Assuming you are committed to this and go ahead, I would divide it into two parts: 1. a graphics demo -- make it clear its a demonstration so they have an appreciation of what is possible and you are not actually teaching anything in this portion. 2. Teach them how to install R, run the above two commands (substituting in different colors), how to exit and point out that there are many tutorials in: http://cran.r-project.org/other-docs.html and they can pick one they like (since the official documents will be over their head). If you do that then perhaps a small number will have sufficient interest to try it some more at home but I wouldn't be surprised if none do and that most or all would prefer something with more immediate gratification. -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
<...snipped>
>> I anticipate keeping things very simple: >> --objects and the fact that there is stuff inside them. str(), head(), tail() >> --how to get data into R >> --dataframes, as I imagine they will mostly be using single, >> "rectangular" datasets >> --a lot of graphics (I can't imagine that plot(force, acceleration) >> is beyond a high-schooler's capability.) >> --simple descriptive statistics >> --maybe t-tests, chi-square tests, and simple linear regression. >> > > I have some experience in this and would have to agree with Indrajit > that this is not a good idea. > > When I tried to teach R to a high school student it was not very > successful. Certainly based on that experience the list above is way > too complex. Don't teach anything on that list at all. The number of > concepts involved in that is simply overwhelming. Oh amen amen! I'd go farther: It's overwhelming for college students. Farther yet: I've met very few scientists and engineers who understand what a standard deviation is. Fewer still who understand the difference between a sample statistic and a population parameter for which it's an estimate. This approach to "basic" statistics is (imho) symptomatic of why our discipline is so widely disliked and misunderstood. Cheers, Bert Also avoid teaching > anything that requires complex installation if you want them to be > able to carry it forward by themselves. > > I would expect the reaction would be that most will have no interest > and the ones that do will be frustrated by the large number of > concepts needed to get going. > > The only part that seemed to trigger any interest was when I showed > the large list of colors available in colors() and then playing with > inserting different colors in: > > colors() > plot(1:5, col = "violetred") > > Assuming you are committed to this and go ahead, I would divide it > into two parts: > > 1. a graphics demo -- make it clear its a demonstration so they have > an appreciation of what is possible and you are not actually teaching > anything in this portion. > > 2. Teach them how to install R, run the above two commands > (substituting in different colors), how to exit and point out that > there are many tutorials in: > http://cran.r-project.org/other-docs.html > and they can pick one they like (since the official documents will be > over their head). > > If you do that then perhaps a small number will have sufficient > interest to try it some more at home but I wouldn't be surprised if > none do and that most or all would prefer something with more > immediate gratification. > > -- > Statistics & Software Consulting > GKX Group, GKX Associates Inc. > tel: 1-877-GKX-GROUP > email: ggrothendieck at gmail.com > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
Thanks all for the excellent thought-provoking comments.
I want to clarify that these students are, for good or for ill, already doing all these analytical and graphical things for their projects. They are doing them with Excel and SPSS. One of my goals would be to teach them how they can be done (and I think done better) in R. Better for many reasons, not least of which is the reproducibility offered by lines of saved code. It seems that many (not all) on the list agree with the science teachers that R is too difficult for high school students. Is R intrinsically more difficult to learn than commercial spreadsheet software? If so, why? Or is the issue that it is difficult to change to R after many years experience in the mind-set of spreadsheets? If a child was "brought up" on R for math/stats, in a developmentally progressive way, instead of Excel or a graphing calculator, would he/she perceive it as difficult? Are the intrinsic cognitive differences between high schoolers, college students, and graduate students substantial enough to explain why the last can learn R and the first can't? Or is it a matter of exposure, opportunity, etc? Indrajit, I'm curious: given your preference for hand-drawn graphs for learners (a very good point), why is Excel "fine" but R not? At any rate, I should probably migrate this thread over to the Teaching SIG listserve, which I didn't know about before. Thanks again. --Chris Christopher W. Ryan, MD SUNY Upstate Medical University Clinical Campus at Binghamton 425 Robinson Street, Binghamton, NY 13904 cryanatbinghamtondotedu "Observation is a more powerful force than you could possibly reckon. The invisible, the overlooked, and the unobserved are the most in danger of reaching the end of the spectrum. They lose the last of their light. >From there, anything can happen . . ." [God, in "Joan of Arcadia," episode entitled, "The Uncertainty Principle."] Bert Gunter wrote: > <...snipped> > >>> I anticipate keeping things very simple: >>> --objects and the fact that there is stuff inside them. str(), head(), tail() >>> --how to get data into R >>> --dataframes, as I imagine they will mostly be using single, >>> "rectangular" datasets >>> --a lot of graphics (I can't imagine that plot(force, acceleration) >>> is beyond a high-schooler's capability.) >>> --simple descriptive statistics >>> --maybe t-tests, chi-square tests, and simple linear regression. >>> >> >> I have some experience in this and would have to agree with Indrajit >> that this is not a good idea. >> >> When I tried to teach R to a high school student it was not very >> successful. Certainly based on that experience the list above is way >> too complex. Don't teach anything on that list at all. The number of >> concepts involved in that is simply overwhelming. > > Oh amen amen! > > I'd go farther: It's overwhelming for college students. > > Farther yet: I've met very few scientists and engineers who understand > what a standard deviation is. Fewer still who understand the > difference between a sample statistic and a population parameter for > which it's an estimate. > > This approach to "basic" statistics is (imho) symptomatic of why our > discipline is so widely disliked and misunderstood. > > Cheers, > Bert > > Also avoid teaching >> anything that requires complex installation if you want them to be >> able to carry it forward by themselves. >> >> I would expect the reaction would be that most will have no interest >> and the ones that do will be frustrated by the large number of >> concepts needed to get going. >> >> The only part that seemed to trigger any interest was when I showed >> the large list of colors available in colors() and then playing with >> inserting different colors in: >> >> colors() >> plot(1:5, col = "violetred") >> >> Assuming you are committed to this and go ahead, I would divide it >> into two parts: >> >> 1. a graphics demo -- make it clear its a demonstration so they have >> an appreciation of what is possible and you are not actually teaching >> anything in this portion. >> >> 2. Teach them how to install R, run the above two commands >> (substituting in different colors), how to exit and point out that >> there are many tutorials in: >> http://cran.r-project.org/other-docs.html >> and they can pick one they like (since the official documents will be >> over their head). >> >> If you do that then perhaps a small number will have sufficient >> interest to try it some more at home but I wouldn't be surprised if >> none do and that most or all would prefer something with more >> immediate gratification. >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> ______________________________________________ >> [hidden email] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
Christopher,
I originally thought about writing off list to avoid a plethora of babble. However here goes. I don't see any reason why good students can 't learn the fundamentals of R. It has lots of advance methods that perhaps are too complex to handle for younger - less experienced people. On the other hand, if your students are engaged and already doing graphs and other spreadsheet applications than why not go ahead and experiment with some of the functionality R has to offer. The critics seem to forget that inner city kids in CA were exceptional in their ability to learn advanced placement calculus when pushed to learn. The US lags far behind the international community in math skills, so if R can help them catch up, go ahead and give it a try. I'd pick some elementary concepts first to allow them to become familiar with the software. A series of exercises in learning what a vector is, then how vectors can contain more than one attribute. Show then how, to add column, how to add rows, develop simple arithmetic problems, etc. then move to data.frames and perhaps, lists with mixed numeric and categorical attributes. Demonstrate the apply functions, trellis (or lattice) and scatter plots etc. My two cents, Steve Friedman Ph. D. Ecologist / Spatial Statistical Analyst Everglades and Dry Tortugas National Park 950 N Krome Ave (3rd Floor) Homestead, Florida 33034 [hidden email] Office (305) 224 - 4282 Fax (305) 224 - 4147 "Christopher W. Ryan" <cryan@binghamton To .edu> R-help <[hidden email]> Sent by: cc r-help-bounces@r- project.org Subject Re: [R] introducing R to high school students 04/18/2012 10:25 AM Thanks all for the excellent thought-provoking comments. I want to clarify that these students are, for good or for ill, already doing all these analytical and graphical things for their projects. They are doing them with Excel and SPSS. One of my goals would be to teach them how they can be done (and I think done better) in R. Better for many reasons, not least of which is the reproducibility offered by lines of saved code. It seems that many (not all) on the list agree with the science teachers that R is too difficult for high school students. Is R intrinsically more difficult to learn than commercial spreadsheet software? If so, why? Or is the issue that it is difficult to change to R after many years experience in the mind-set of spreadsheets? If a child was "brought up" on R for math/stats, in a developmentally progressive way, instead of Excel or a graphing calculator, would he/she perceive it as difficult? Are the intrinsic cognitive differences between high schoolers, college students, and graduate students substantial enough to explain why the last can learn R and the first can't? Or is it a matter of exposure, opportunity, etc? Indrajit, I'm curious: given your preference for hand-drawn graphs for learners (a very good point), why is Excel "fine" but R not? At any rate, I should probably migrate this thread over to the Teaching SIG listserve, which I didn't know about before. Thanks again. --Chris Christopher W. Ryan, MD SUNY Upstate Medical University Clinical Campus at Binghamton 425 Robinson Street, Binghamton, NY 13904 cryanatbinghamtondotedu "Observation is a more powerful force than you could possibly reckon. The invisible, the overlooked, and the unobserved are the most in danger of reaching the end of the spectrum. They lose the last of their light. >From there, anything can happen . . ." [God, in "Joan of Arcadia," episode entitled, "The Uncertainty Principle."] Bert Gunter wrote: > <...snipped> > >>> I anticipate keeping things very simple: >>> --objects and the fact that there is stuff inside them. str(), head(), tail() >>> --how to get data into R >>> --dataframes, as I imagine they will mostly be using single, >>> "rectangular" datasets >>> --a lot of graphics (I can't imagine that plot(force, acceleration) >>> is beyond a high-schooler's capability.) >>> --simple descriptive statistics >>> --maybe t-tests, chi-square tests, and simple linear regression. >>> >> >> I have some experience in this and would have to agree with Indrajit >> that this is not a good idea. >> >> When I tried to teach R to a high school student it was not very >> successful. Certainly based on that experience the list above is way >> too complex. Don't teach anything on that list at all. The number of >> concepts involved in that is simply overwhelming. > > Oh amen amen! > > I'd go farther: It's overwhelming for college students. > > Farther yet: I've met very few scientists and engineers who understand > what a standard deviation is. Fewer still who understand the > difference between a sample statistic and a population parameter for > which it's an estimate. > > This approach to "basic" statistics is (imho) symptomatic of why our > discipline is so widely disliked and misunderstood. > > Cheers, > Bert > > Also avoid teaching >> anything that requires complex installation if you want them to be >> able to carry it forward by themselves. >> >> I would expect the reaction would be that most will have no interest >> and the ones that do will be frustrated by the large number of >> concepts needed to get going. >> >> The only part that seemed to trigger any interest was when I showed >> the large list of colors available in colors() and then playing with >> inserting different colors in: >> >> colors() >> plot(1:5, col = "violetred") >> >> Assuming you are committed to this and go ahead, I would divide it >> into two parts: >> >> 1. a graphics demo -- make it clear its a demonstration so they have >> an appreciation of what is possible and you are not actually teaching >> anything in this portion. >> >> 2. Teach them how to install R, run the above two commands >> (substituting in different colors), how to exit and point out that >> there are many tutorials in: >> http://cran.r-project.org/other-docs.html >> and they can pick one they like (since the official documents will be >> over their head). >> >> If you do that then perhaps a small number will have sufficient >> interest to try it some more at home but I wouldn't be surprised if >> none do and that most or all would prefer something with more >> immediate gratification. >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> >> ______________________________________________ >> [hidden email] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> and provide commented, minimal, self-contained, reproducible code. > > > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Indrajit Sen Gupta
Indrajit, As a former math teacher I understand your concerns wholly. My perspective is that this must be approached with caution so you don't miss out on the important learning but I think with proper guidance and scaffolding this could be an amazing tool. We already using the graphing capabilities of the TI-(insert number here) to demonstrate graphing problems, why not put a sophisticated tool in their hands that may be very useful to them in the future and at least introduce them to programming. Students are capable of some pretty cool and creative things if we give them the tools and support to allow them to be creative (I mean which one of use didn't program out ti-81s to play video games?). Your point of the learning being hindered isn't lost. This has to be approached delicately so R isn't just another program spitting out answers/graphs. Chris's question sounds like a one time intro thing so this may be a moot pint, however if the R learning is more long term, I would suggest some sort of lab set up (maybe a "lab day") each week that augments and compliments the standard curriculum. One thing I may advise against is the "--maybe t-tests, chi-square tests, and simple linear regression." as this is usually far beyond the scope of high school curriculum (at least to my knowledge). Could I also suggest you do some eye candy (not much but some) where you show a few of the things R is capable of to get their interests peaked (I consider this like playing guitar; I learned it because Hendrix played sweet stuff not because I liked playing basic chords and scales; I plugged through the elementary stuff because I knew Hendrix, Clapton, and Page were within my grasp if I kept going). Here's a few suggestions:http://paulbutler.org/archives/visualizing-facebook-friends/ http://blog.revolutionanalytics.com/2012/01/nyt-uses-r-to-map-the-1.html http://blog.revolutionanalytics.com/2009/11/choropleth-challenge-result.html http://www.r-bloggers.com/visualize-your-facebook-friends-network-with-r/ http://www.r-bloggers.com/see-the-wind/ http://www.r-bloggers.com/mapped-british-and-spanish-shipping-1750-1800/ And also I'd introduce them to Anthony Damico's "r twotorials" as it provides catchy short tutorials on how to do basic stuff:http://www.twotorials.com/2012/04/ I wish I knew R when I was a math teacher and applaud any effort to engage students in authentic learning with powerful tools that they may use later on. I would encourage physics teachers to incorporate R too. Tyler Rinker From: [hidden email] To: [hidden email] Subject: Re: [R] introducing R to high school students Hi Chris, I am not sure, whether introducing R to High School students would be a good idea as I feel we should encourage students to sketch the graphs in paper to get their concepts right. Excel is fine, but - if I write an equation on the board, will the student be able to visualize its graph? Allowing students to use software to plot graphs at a very early age may hinder that learning. What I would focus on (as the teacher pointed out - that they may not be able to write code) - is being able to write simple codes to get a grasp on programming (they can use QBASIC which is one of the simplest programming softwares). R to my mind should be introduced at an undergraduate level - where they are able to use its real power (vectors, matrices, graphics etc.). Thats my view :) Regards, Indrajit ________________________________ From: Christopher W Ryan <[hidden email]> To: R-help <[hidden email]> Sent: Wednesday, April 18, 2012 8:16 AM Subject: [R] introducing R to high school students I participate peripherally on a listserve for middle- and high-school science teachers. Sometimes questions about graphing or data analysis come up. I never miss an opportunity to advocate for R. However, the teachers are often skeptical that their students would be able to issue commands or write a little code; they think it would be too difficult. Perhaps this stems from the Microsoft- and spreadsheet-centered, pointy-clicky culture prevalent in most US public schools. Then again, I have little experience teaching this age group, besides my own kids and my Science Olympiad team, so I respect their concerns and expertise. I don't know yet what software they generally use, but I suspect MS Excel and SPSS. Now I have to put my money where my mouth is. I've offered to visit a high school and introduce R to some fairly advanced students participating in a longitudinal 3-year science research class. I anticipate keeping things very simple: --objects and the fact that there is stuff inside them. str(), head(), tail() --how to get data into R --dataframes, as I imagine they will mostly be using single, "rectangular" datasets --a lot of graphics (I can't imagine that plot(force, acceleration) is beyond a high-schooler's capability.) --simple descriptive statistics --maybe t-tests, chi-square tests, and simple linear regression. Alas, probably more than we would have time to cover. Has anyone done anything with R in high schools? Thanks. --Chris Ryan SUNY Upstate Medical University Binghamton Clinical Campus ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
I think that mostly avoiding the statistics and matrix capabilities is wise. You might want to (re-)read Burns' article on Spreadsheet Addiction for help in justifying the effort required to learn R.
In that vein, there is a classic experiment where a small ball is rolled down an inclined pane and the time required to roll various distances is measured. One way to investigate fitting this data is to square the time in the spreadsheet. (The other is to use the built-in polynomial regression.) If there is a missing value in the input time, the squared cell will be zero. You can overcome this by manually putting an =NA() in the missing cell, but that is tedious when there is lots of data, and it gets even more tedious when you want to throw out the whole data record while remembering which records were used in the final analysis. R allows this and similar steps to be automated. I also think running some examples of plots like tiled layouts, colored maps, boxplots, or 3d interactive cloud graphs may provide good brainstorming material for data representation. --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<[hidden email]> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity. "Christopher W. Ryan" <[hidden email]> wrote: >Thanks all for the excellent thought-provoking comments. > >I want to clarify that these students are, for good or for ill, already >doing all these analytical and graphical things for their projects. >They >are doing them with Excel and SPSS. One of my goals would be to teach >them how they can be done (and I think done better) in R. Better for >many reasons, not least of which is the reproducibility offered by >lines >of saved code. > >It seems that many (not all) on the list agree with the science >teachers >that R is too difficult for high school students. Is R intrinsically >more difficult to learn than commercial spreadsheet software? If so, >why? Or is the issue that it is difficult to change to R after many >years experience in the mind-set of spreadsheets? If a child was >"brought up" on R for math/stats, in a developmentally progressive way, >instead of Excel or a graphing calculator, would he/she perceive it as >difficult? > >Are the intrinsic cognitive differences between high schoolers, college >students, and graduate students substantial enough to explain why the >last can learn R and the first can't? Or is it a matter of exposure, >opportunity, etc? > >Indrajit, I'm curious: given your preference for hand-drawn graphs for >learners (a very good point), why is Excel "fine" but R not? > >At any rate, I should probably migrate this thread over to the Teaching >SIG listserve, which I didn't know about before. > >Thanks again. > >--Chris >Christopher W. Ryan, MD >SUNY Upstate Medical University Clinical Campus at Binghamton >425 Robinson Street, Binghamton, NY 13904 >cryanatbinghamtondotedu > >"Observation is a more powerful force than you could possibly reckon. >The invisible, the overlooked, and the unobserved are the most in >danger >of reaching the end of the spectrum. They lose the last of their light. >>From there, anything can happen . . ." [God, in "Joan of Arcadia," >episode entitled, "The Uncertainty Principle."] > >Bert Gunter wrote: >> <...snipped> >> >>>> I anticipate keeping things very simple: >>>> --objects and the fact that there is stuff inside them. str(), >head(), tail() >>>> --how to get data into R >>>> --dataframes, as I imagine they will mostly be using single, >>>> "rectangular" datasets >>>> --a lot of graphics (I can't imagine that plot(force, >acceleration) >>>> is beyond a high-schooler's capability.) >>>> --simple descriptive statistics >>>> --maybe t-tests, chi-square tests, and simple linear regression. >>>> >>> >>> I have some experience in this and would have to agree with Indrajit >>> that this is not a good idea. >>> >>> When I tried to teach R to a high school student it was not very >>> successful. Certainly based on that experience the list above is >way >>> too complex. Don't teach anything on that list at all. The number >of >>> concepts involved in that is simply overwhelming. >> >> Oh amen amen! >> >> I'd go farther: It's overwhelming for college students. >> >> Farther yet: I've met very few scientists and engineers who >understand >> what a standard deviation is. Fewer still who understand the >> difference between a sample statistic and a population parameter for >> which it's an estimate. >> >> This approach to "basic" statistics is (imho) symptomatic of why our >> discipline is so widely disliked and misunderstood. >> >> Cheers, >> Bert >> >> Also avoid teaching >>> anything that requires complex installation if you want them to be >>> able to carry it forward by themselves. >>> >>> I would expect the reaction would be that most will have no interest >>> and the ones that do will be frustrated by the large number of >>> concepts needed to get going. >>> >>> The only part that seemed to trigger any interest was when I showed >>> the large list of colors available in colors() and then playing with >>> inserting different colors in: >>> >>> colors() >>> plot(1:5, col = "violetred") >>> >>> Assuming you are committed to this and go ahead, I would divide it >>> into two parts: >>> >>> 1. a graphics demo -- make it clear its a demonstration so they have >>> an appreciation of what is possible and you are not actually >teaching >>> anything in this portion. >>> >>> 2. Teach them how to install R, run the above two commands >>> (substituting in different colors), how to exit and point out that >>> there are many tutorials in: >>> http://cran.r-project.org/other-docs.html >>> and they can pick one they like (since the official documents will >be >>> over their head). >>> >>> If you do that then perhaps a small number will have sufficient >>> interest to try it some more at home but I wouldn't be surprised if >>> none do and that most or all would prefer something with more >>> immediate gratification. >>> >>> -- >>> Statistics & Software Consulting >>> GKX Group, GKX Associates Inc. >>> tel: 1-877-GKX-GROUP >>> email: ggrothendieck at gmail.com >>> >>> ______________________________________________ >>> [hidden email] mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> >> >> > >______________________________________________ >[hidden email] mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
On Apr 18, 2012, at 12:31 PM, Jeff Newmiller wrote: > I think that mostly avoiding the statistics and matrix capabilities > is wise. You might want to (re-)read Burns' article on Spreadsheet > Addiction for help in justifying the effort required to learn R. > > In that vein, there is a classic experiment where a small ball is > rolled down an inclined pane and the time required to roll various > distances is measured. I'll say it's classic. First done by Galileo: http://www.u-picardie.fr/~dellis/Documents/PhysicsEducation/Reconstruction%20of%20Galileo%20Galilei.pdf > One way to investigate fitting this data is to square the time in > the spreadsheet. Another way is to examine first and second differences in distances reached after successive equal intervals. The diff() function is rather handy in this effort. Back to the matter at hand, ... I see no convincing reason to consider R any more complex as a computer language than is Logo. The suggestion to use color in graphics output seems to be in accord with what I have seen as far as pedagogic recommendations for using Logo as a teaching platform. -- David Winsemius. > (The other is to use the built-in polynomial regression.) If there > is a missing value in the input time, the squared cell will be zero. > You can overcome this by manually putting an =NA() in the missing > cell, but that is tedious when there is lots of data, and it gets > even more tedious when you want to throw out the whole data record > while remembering which records were used in the final analysis. R > allows this and similar steps to be automated. > > I also think running some examples of plots like tiled layouts, > colored maps, boxplots, or 3d interactive cloud graphs may provide > good brainstorming material for data representation. > --------------------------------------------------------------------------- > Jeff Newmiller The ..... ..... Go > Live... > DCN:<[hidden email]> Basics: ##.#. ##.#. > Live Go... > Live: OO#.. Dead: OO#.. > Playing > Research Engineer (Solar/Batteries O.O#. #.O#. with > /Software/Embedded Controllers) .OO#. .OO#. > rocks...1k > --------------------------------------------------------------------------- > Sent from my phone. Please excuse my brevity. > > "Christopher W. Ryan" <[hidden email]> wrote: > >> Thanks all for the excellent thought-provoking comments. >> >> I want to clarify that these students are, for good or for ill, >> already >> doing all these analytical and graphical things for their projects. >> They >> are doing them with Excel and SPSS. One of my goals would be to teach >> them how they can be done (and I think done better) in R. Better for >> many reasons, not least of which is the reproducibility offered by >> lines >> of saved code. >> >> It seems that many (not all) on the list agree with the science >> teachers >> that R is too difficult for high school students. Is R intrinsically >> more difficult to learn than commercial spreadsheet software? If so, >> why? Or is the issue that it is difficult to change to R after many >> years experience in the mind-set of spreadsheets? If a child was >> "brought up" on R for math/stats, in a developmentally progressive >> way, >> instead of Excel or a graphing calculator, would he/she perceive it >> as >> difficult? >> >> Are the intrinsic cognitive differences between high schoolers, >> college >> students, and graduate students substantial enough to explain why the >> last can learn R and the first can't? Or is it a matter of exposure, >> opportunity, etc? >> >> Indrajit, I'm curious: given your preference for hand-drawn graphs >> for >> learners (a very good point), why is Excel "fine" but R not? >> >> At any rate, I should probably migrate this thread over to the >> Teaching >> SIG listserve, which I didn't know about before. >> >> Thanks again. >> >> --Chris >> Christopher W. Ryan, MD >> SUNY Upstate Medical University Clinical Campus at Binghamton >> 425 Robinson Street, Binghamton, NY 13904 >> cryanatbinghamtondotedu >> >> "Observation is a more powerful force than you could possibly reckon. >> The invisible, the overlooked, and the unobserved are the most in >> danger >> of reaching the end of the spectrum. They lose the last of their >> light. >>> From there, anything can happen . . ." [God, in "Joan of Arcadia," >> episode entitled, "The Uncertainty Principle."] >> >> Bert Gunter wrote: >>> <...snipped> >>> >>>>> I anticipate keeping things very simple: >>>>> --objects and the fact that there is stuff inside them. str(), >> head(), tail() >>>>> --how to get data into R >>>>> --dataframes, as I imagine they will mostly be using single, >>>>> "rectangular" datasets >>>>> --a lot of graphics (I can't imagine that plot(force, >> acceleration) >>>>> is beyond a high-schooler's capability.) >>>>> --simple descriptive statistics >>>>> --maybe t-tests, chi-square tests, and simple linear regression. >>>>> >>>> >>>> I have some experience in this and would have to agree with >>>> Indrajit >>>> that this is not a good idea. >>>> >>>> When I tried to teach R to a high school student it was not very >>>> successful. Certainly based on that experience the list above is >> way >>>> too complex. Don't teach anything on that list at all. The number >> of >>>> concepts involved in that is simply overwhelming. >>> >>> Oh amen amen! >>> >>> I'd go farther: It's overwhelming for college students. >>> >>> Farther yet: I've met very few scientists and engineers who >> understand >>> what a standard deviation is. Fewer still who understand the >>> difference between a sample statistic and a population parameter for >>> which it's an estimate. >>> >>> This approach to "basic" statistics is (imho) symptomatic of why our >>> discipline is so widely disliked and misunderstood. >>> >>> Cheers, >>> Bert >>> >>> Also avoid teaching >>>> anything that requires complex installation if you want them to be >>>> able to carry it forward by themselves. >>>> >>>> I would expect the reaction would be that most will have no >>>> interest >>>> and the ones that do will be frustrated by the large number of >>>> concepts needed to get going. >>>> >>>> The only part that seemed to trigger any interest was when I showed >>>> the large list of colors available in colors() and then playing >>>> with >>>> inserting different colors in: >>>> >>>> colors() >>>> plot(1:5, col = "violetred") >>>> >>>> Assuming you are committed to this and go ahead, I would divide it >>>> into two parts: >>>> >>>> 1. a graphics demo -- make it clear its a demonstration so they >>>> have >>>> an appreciation of what is possible and you are not actually >> teaching >>>> anything in this portion. >>>> >>>> 2. Teach them how to install R, run the above two commands >>>> (substituting in different colors), how to exit and point out that >>>> there are many tutorials in: >>>> http://cran.r-project.org/other-docs.html >>>> and they can pick one they like (since the official documents will >> be >>>> over their head). >>>> >>>> If you do that then perhaps a small number will have sufficient >>>> interest to try it some more at home but I wouldn't be surprised if >>>> none do and that most or all would prefer something with more >>>> immediate gratification. >>>> >>>> -- >>>> Statistics & Software Consulting >>>> GKX Group, GKX Associates Inc. >>>> tel: 1-877-GKX-GROUP >>>> email: ggrothendieck at gmail.com > David Winsemius, MD West Hartford, CT ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
> Now I have to put my money where my mouth is. I've offered to visit a
> high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. I think those are good topics to cover, but the order is wrong - start with graphics. They are immediately useful and you can start with built in datasets (although I'd recommend finding a package with more interesting/bigger datasets than the base packages). Once you've shown them how to use graphics to understand data you can talk more about how it works - what is a dataframe, how you load data in R, etc. That's the path I follow when I teach R (http://stat405.had.co.nz/, http://vita.had.co.nz/papers/assessment.html), and I find it to be successful at keeping students motivated enough to work through the initial frustrations of learning a new language. R is not too difficult for high-school students to learn, but you need to make sure you provide them with tools to do things that they're interested in - finding interesting problems that they _want_ to solve is most of the battle. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/ ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
> -----Original Message----- > From: [hidden email] [mailto:[hidden email]] On Behalf > Of Hadley Wickham > Sent: Wednesday, April 18, 2012 10:37 AM > To: Christopher W Ryan > Cc: R-help > Subject: Re: [R] introducing R to high school students > > > Now I have to put my money where my mouth is. I've offered to visit a > > high school and introduce R to some fairly advanced students > > participating in a longitudinal 3-year science research class. > > > > I anticipate keeping things very simple: > > --objects and the fact that there is stuff inside them. str(), head(), tail() > > --how to get data into R > > --dataframes, as I imagine they will mostly be using single, > > "rectangular" datasets > > --a lot of graphics (I can't imagine that plot(force, acceleration) > > is beyond a high-schooler's capability.) > > --simple descriptive statistics > > --maybe t-tests, chi-square tests, and simple linear regression. > > I think those are good topics to cover, but the order is wrong - start > with graphics. They are immediately useful and you can start with > built in datasets (although I'd recommend finding a package with more > interesting/bigger datasets than the base packages). Once you've > shown them how to use graphics to understand data you can talk more > about how it works - what is a dataframe, how you load data in R, etc. > > That's the path I follow when I teach R (http://stat405.had.co.nz/, > http://vita.had.co.nz/papers/assessment.html), and I find it to be > successful at keeping students motivated enough to work through the > initial frustrations of learning a new language. R is not too > difficult for high-school students to learn, but you need to make sure > you provide them with tools to do things that they're interested in - > finding interesting problems that they _want_ to solve is most of the > battle. If the students are in a "science research" class, does that mean they have data from their own research that they would want to understand better? I think that would be much more motivating than anything else. "If you want to build a ship, don't drum up the men to gather wood, divide the work and give orders. Instead, teach them to yearn for the vast and endless sea." [Antoine de St. Exupery] Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com > > Hadley > > -- > Assistant Professor / Dobelman Family Junior Chair > Department of Statistics / Rice University > http://had.co.nz/ > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
> If the students are in a "science research" class, does that mean they
> have data from their own research that they would want to understand > better? I think that would be much more motivating than anything else. It might depends on the class - most high school science experiments aren't that compelling. Depending on the audience you might find publicly available datasets to be more interesting - there's plenty of stuff on sports, console games, ... that they might find more interesting. > "If you want to build a ship, don't drum up the men to gather wood, > divide the work and give orders. Instead, teach them to yearn for the > vast and endless sea." [Antoine de St. Exupery] Exactly - I love that quote. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/ ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
see below.
On Wed, Apr 18, 2012 at 2:39 PM, Hadley Wickham <[hidden email]> wrote: >> If the students are in a "science research" class, does that mean they >> have data from their own research that they would want to understand >> better? I think that would be much more motivating than anything else. > > It might depends on the class - most high school science experiments > aren't that compelling. Yes. But then , one should try to give them ideas for better experiments! One thing I would want to do is learn them the basics (very____ basics!) of factorial experiments, and then let them use it for bettering the design of, foe example, paper planes. (or they could make soap in the chem lab and use factorial experiments to better the process) Kjetil Depending on the audience you might find > publicly available datasets to be more interesting - there's plenty of > stuff on sports, console games, ... that they might find more > interesting. > >> "If you want to build a ship, don't drum up the men to gather wood, >> divide the work and give orders. Instead, teach them to yearn for the >> vast and endless sea." [Antoine de St. Exupery] > > Exactly - I love that quote. > > Hadley > > -- > Assistant Professor / Dobelman Family Junior Chair > Department of Statistics / Rice University > http://had.co.nz/ > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
In reply to this post by Christopher W. Ryan
Chris,
Don't get me wrong - I have nothing against learning R at an early age. However, I feel at a school level, the focus should be a bit more on programming. Here are some reasons why would not recommend R at school level: 1. At school we seldom deal with lot of data - the focus is more on concepts. Excel is an excellent tool and no matter how much we love or hate it - we will be using Excel a lot in our lives. 2. R language is a very high level language. To get a good grasp on programming - I would recommend any one of QBASIC, C or JAVA (Java might be a bit too much given OOP is not easy). Learn stuff the hard way - that way your fundamentals get strong. Even Excel VBA is a very powerful language - if you can incorporate that in your course - nothing like it. You will be churning out data scientists from your school. 3. The danger of introducing R too early - similar to introducing calculators to kids who are learning basic mental maths. They get too dependent on tools Hope this clears my point of view. Regards, Indrajit ________________________________ From: Christopher W. Ryan <[hidden email]> To: R-help <[hidden email]> Sent: Wednesday, April 18, 2012 7:55 PM Subject: Re: [R] introducing R to high school students Indrajit, I'm curious: given your preference for hand-drawn graphs for learners (a very good point), why is Excel "fine" but R not? [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
On 22/04/12 15:29, Indrajit Sengupta wrote:
<SNIP> > 1. At school we seldom deal with lot of data - the focus is more on concepts. Excel is an excellent tool That is at best debatable, and IMHO just plain incorrect. I firmly believe that Excel is a ***TERRIBLE*** tool. > and no matter how much we love or hate it - we will be using Excel a lot in our lives. This is not (unfortunately IMHO) debatable. It is all too sadly true. For most people at least. (Not for my very good self. I can get away with eschewing Excel. Most people are not lucky enough to have that option.) <SNIP> I think much of the remainder of the post was highly disputable as well, but I will desist at this point. cheers, Rolf Turner ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
Why do you think Excel is a terrible tool? In what ways have you tried to use Excel and it has failed you?
Regards, Indrajit ________________________________ From: Rolf Turner <[hidden email]> Cc: R-help <[hidden email]> Sent: Sunday, April 22, 2012 9:25 AM Subject: Re: [R] introducing R to high school students On 22/04/12 15:29, Indrajit Sengupta wrote: <SNIP> > 1. At school we seldom deal with lot of data - the focus is more on concepts. Excel is an excellent tool That is at best debatable, and IMHO just plain incorrect. I firmly believe that Excel is a ***TERRIBLE*** tool. > and no matter how much we love or hate it - we will be using Excel a lot in our lives. This is not (unfortunately IMHO) debatable. It is all too sadly true. For most people at least. (Not for my very good self. I can get away with eschewing Excel. Most people are not lucky enough to have that option.) <SNIP> I think much of the remainder of the post was highly disputable as well, but I will desist at this point. cheers, Rolf Turner [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
Bert,
What you are saying - is a problem with people who are using Excel. It is not Excel's problem that people are sending data in an unstructured way. I agree - Excel may not be the right tool when you are doing some complicated data analysis (like for e.g. statistical modeling) - but that is not what Excel was built for. The power of Excel lies in being able to use it to explore data, represent and present your analysis. When exploring data, yes it may not be very useful beyond univariates and bivariates - but that is your starting point in EDA where you need to generate hypotheses about your data. I have been in the field of analytics for almost 7 years now, though we have embraced technologies like SAS, R, SPSS, Spotfire, etc., the power and importance of Excel in our lives has never been lost to us. Its a question of whether are you capable enough to use it. Regards, Indrajit ________________________________ From: Bert Gunter <[hidden email]> Cc: Rolf Turner <[hidden email]> Sent: Sunday, April 22, 2012 11:07 AM Subject: Re: [R] introducing R to high school students I would like to slightly clarify and echo Rolf's comment: Excel is a terrible tool for data analysis. Maybe it's a good tool for keeping track of your car's repair history... but not for data analysis. I could go on at great length why, but let me just focus on one aspect that drives me and other statisticians in my group crazy when we deal with scientists who send us data in Excel: the data are frequently a mess! By this I mean that they are often stored in crazy ways, with plots and summaries sprinkled around, capital letters and small letters mixed, missing values coded arbitrarily e.g.(99999 ), and so forth. As someone I know once commented, it's a puzzle to get the data extracted in a form susceptible to analysis. Why is this? -- because Excel enforces no structure. It's **cell-based** (duhhhh), so users can throw in the data anyway they see fit, which frequently is pretty unfit. This is not just a minor issue, imho. Not having data in a reasonable structure limits what one can do for data analysis and graphics. This promulgates the inadequate and frequently awful paradigms that one sees throughout science (e.g. bar charts with 1 se bars sticking up out of them). The widespread use of Excel for "serious' scientific and engineering data analysis is a near tragedy. All IMHO, of course. Cheers, Bert On Sat, Apr 21, 2012 at 9:45 PM, Indrajit Sengupta > Why do you think Excel is a terrible tool? In what ways have you tried to use Excel and it has failed you? > > Regards, > Indrajit > > > ________________________________ > From: Rolf Turner <[hidden email]> > > Cc: R-help <[hidden email]> > Sent: Sunday, April 22, 2012 9:25 AM > Subject: Re: [R] introducing R to high school students > > On 22/04/12 15:29, Indrajit Sengupta wrote: > > <SNIP> >> 1. At school we seldom deal with lot of data - the focus is more on concepts. Excel is an excellent tool > That is at best debatable, and IMHO just plain incorrect. I firmly believe > that Excel is a ***TERRIBLE*** tool. >> and no matter how much we love or hate it - we will be using Excel a lot in our lives. > > This is not (unfortunately IMHO) debatable. It is all too sadly true. For most > people at least. (Not for my very good self. I can get away with eschewing > Excel. Most people are not lucky enough to have that option.) > > <SNIP> > > I think much of the remainder of the post was highly disputable as well, > but I will desist at this point. > > cheers, > > Rolf Turner > [[alternative HTML version deleted]] > > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
I have to agree that Excel is a poor tool for "serious scientific and
engineering data analysis" (love the phrase.) I too have spent way too much time beating Excel files into submission, with workarounds and manipulations, just to be able to do anything useful with them. I'm told that one can to some degree impose structure on Excel data entry, but I don't know how, and no users ever seem to set up their spreadsheets that way. Somehow, a reasonable tool for business (I suppose, not being a businessman), has infiltrated the scientific world as well. That's really the motivation for my proposal to my science teacher colleague. I want to introduce budding scientists to the idea that there is a better tool for data analysis, even for exploratory analysis and univariates and bivariates, which R does very handily. Why start an analysis in Excel only to have to switch to something else for the latter half? And this will lead inevitably into conversations about better ways to record, store, and share data. And it ties into concepts of collaboration and reproducible research. --Chris Ryan SUNY Upstate Clinical Campus Binghamton, NY ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. |
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