SPSS is more user friendly. You can also consider using PSPP which is an alternative to SPSS but looks exactly like SPSS. It's free and can be run on computers with low configurations as well. I have analysed and published data in two of my recent publications using this software.
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Spss is much simple if you know the basics. But the coding is much easier in excel . SPSS is exclusively made for statstical computing . Excel can be used for preparing long coding sheets. My opinion is a perfect blend of both. But inferential statistics spss is the winner
Si la base de datos es grande la recomendación sería SPSS, ya que es un software que puede ser de mucha ayuda para gestionar grandes volúmenes de datos.
It doesn't matter what you use, as long as it works. But you're correct, Excel is difficult, as is R :)
Excel has more flexibility, that allows for instance more flexible coding of variables, different file formats and also business like calculations. E.g, referring from one table to another (in same or other file) is easy in Excel with hyperlinks. But also referring to specific cells or cell ranges in one table, e.g. to get a mean value in table A from hundreds of data in table B. That is stil difficult in SPSS.
On the other hand, the flexibility of Excel has its dangers. A cell value in Excell is easy overwritten and many “aids” often have their own will and do something the researcher does not want al all. SPSS is still mainly a column with a variable name and row with respondents and values based system. R does more with modern data formats like JSON or programming like Python. Excel cannot use these and whether SPSS can handle JSON input or Python for data management is unclear to me.
Excel descriptive statistics (frequencies, median and such) are easy and nice graphs and tables can be created instantly.
For tough inferential statistics, SPSS or R are preferred since that is were these tools are created for. And although many calculations could be created as a kind of algorithm in Excel, including possible errors, these are native in SPSS and R And through decades of wide use developments more or less faultless.
However, every answer will depend on your research domain, research question, available data and their data type, and methodology for data analysis.
if you want the mean age a class of 25 students I would go for Excel. If I want to know which variables in a dataset mean something in a regression analysis I would use SPSS.
For ease of use and straightforward data analysis, Excel is often considered more user-friendly than SPSS. Excel's familiar interface and basic statistical functions make it accessible to users with varying levels of statistical expertise. However, SPSS is specifically designed for advanced statistical analysis, offering a more robust set of tools and specialized features. If your analysis involves complex statistical procedures, SPSS may be more powerful, but for simpler analyses and a user-friendly experience, Excel may suffice.
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