On 13 Aug 2003 07:54:49 -0700, [EMAIL PROTECTED] (Donald Burrill) wrote: >Why re-invent the wheel, and have to de-bug it besides? Get one of the >standard statistical analysis packages (SPSS, SAS, MINITAB, ...) and use >the multiple regression routine to fit your data to a suitable model.
I certainly do not want to reinvent the wheel. I will eventually need custom code to run with my data live, but your suggestion of using a commercial package to analyze existing data is a good one. I have heard that Excel can do some statistical analyses. The help file says I need to install the Analysis Toolpak. Do you know how this compares with SPSS or Minitab? Can you recommend a good book on using Excel for this? I also checked the help file for Access. There doesn't seem to be an Analysis Toolpak for Access. I find that odd. Wouldn't people be more likely to store tables of data in Access than Excel? Anyway, Google reports some third party stat packages for Access. Do you know if any of them are any good. My data will be in Access already. >Minitab Inc. in particular offers a 30-day (I think) trial of MINITAB >software: visit <http://www.minitab.com> > >On Wed, 13 Aug 2003, Top Spin wrote in part: > >> I would appreciate suggestions for text books or reference books on >> exponential decay functions, probability distribution functions, and >> the like. ... <snip> >> I am trying to explore whether memory fades exponentially in a way >> that is similar to radioactive isotopes decaying, batteries >> discharging, or light bulbs burning out. I want to write some software >> to gather data and test these ideas, but I need help with the math. I >> want to fit the appropriate function to the test data and then use >> that function to predict future data points. > <snip, the rest> > >An exponential decay function (IIRC) is of the form > > Y = a * e^(bX) > >where Y is the response variable that is thought to decay exponentially, >X is the variable (usually time) with respect to which the decay occurs, >and a and b are real numbers (in practice, rational numbers) to fit >the data. Taking (natural) logarithms, > > Log(Y) = log(a) + bX > >which is of the standard linear form. A simple linear regression >analysis will provide estimates of log(a) and b. > >The textbook references that would help you most are those on regression >analysis. You might start with one of the standards in the field, >Draper & Smith, "Applied regression analysis" (Wiley), which must be in >at least a third edition by now. > >Good luck! -- DFB. > ----------------------------------------------------------------------- > Donald F. Burrill [EMAIL PROTECTED] > 56 Sebbins Pond Drive, Bedford, NH 03110 (603) 626-0816 > >. >. >================================================================= >Instructions for joining and leaving this list, remarks about the >problem of INAPPROPRIATE MESSAGES, and archives are available at: >. http://jse.stat.ncsu.edu/ . >================================================================= -- Spam sink email address, sorry . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
