Today I will share with you the detailed comparison between R vs SPSS. The majority of Student statistics challenge these two programming languages. But this blog will help you clear all your doubts more effectively than ever before.
Let's start with a small comparison between R vs SPSS. Let's look at the R. R language Overview is an open-source programming language based on the S language.
R was developed at the University of Auckland by Ross Ihaka and Robert Gentleman. It is one of the best programming languages for data analysis and data visualization.
The best part of the R programming language is the R that offers the best GUI processors from any other language. The RGui and R studio are usually GUI editors of the R language.
On the other hand, SPSS means "statistical package on social science. Started in the year 1968. The Lateron was acquired by IBM in the year 2009.
After that, it is officially known as IBM SPSS. SPSS is the best software for data cleaning and data analysis. Data can come from any source, i.e. Google Analytics, CRM, or any other database software.
The best part of SPSS is that it can open up all the file formats used for structured data. Some of the most common types are a relational database, SAS, Stata, CSV, and spreadsheet. Let's start the in-depth comparison between R vs SPSS.
Below are the crucial differences between R vs SPSS
I have already given an overview of the programming language R. Let's learn more about programming R. In the year 2000, the University of Auckland officially launched the first edition of R. R focuses mainly on statistical modeling and was Open under the GNU license. R is an open-source programming language. It is also the most preferred programming language for start-ups.
On the other hand, the SPSS was developed at the State University of North Carolina. The primary objective of improving the SPSS was to enable statistics to analyze large quantities of agricultural data. As mentioned above, SPSS means a statistical package for social sciences.
In 1980 the demand for such softwares was growing at a rapid pace. That is why SPSS is created. The year 1976.
SPSS was the first statistical programming language for the computer. Statistical package. It was developed many years ago before it became commercially available for users.
It was developed in 1968 at Stanford University and after eight years, later founded the company SPSS Inc, which launched the official version of SPSS. The year 2009 was purchased by IBM.
R is an open-source programming language. Open source programming languages usually have a large community of active members. That's why R offers faster software updates and continues to add new libraries to provide better functionality for users.
On the other hand, IBM SPSS is not an open-source programming language. It is an IBM commercial product. You can only have a free trial of SPSS for a month. SPSS does not have a community like R and also does not offer quick updates.
The R is written in ancient language age, ie. C, and Fortran. But R also offers object-oriented programming facilities.
On the other hand, the SPSS is written in Java language. SPSS provides the best in class GUI, which is written in Java. Statisticians use R for statistical analysis and interactivity.
Statistical Analysis Decision Trees
When we try R in the trees of statistical analysis decisions. Then, R does not offer many algorithms. Besides, most of the R packages can only apply the sorting and regression. And the worst part of the R packages is that their interface is not so user-friendly.
On the other hand, when we use decision trees in IBM SPSS. Then we find it much better than R because SPSS is more user-friendly, understandable, and easy to use.
R is considered as a less interactive analysis tool than SPSS. But it has a variety of editors who provide GUI support for programming in R. If you want to learn and practice in analysis, then R is much better to learn the steps and commands of analysis.
On the other hand, the SPSS interface is more likely to excel in the spreadsheet. SPSS offers a user-friendly user interface with GUI. If you are familiar with Excel, then you can find it easier than R.
R has an extensive set of packages to modify and optimize graphs. Ggplot2 and R shiny are the most widely used packages in R. It is quite easy to design and write in R language, which allows users to play with data.
On the other hand, SPSS does not offer interactive graphs like R. In SPSS, and you can create only basic and straightforward graphs or graphs.
Both R and SPSS offer almost the same data management. But in the case of R, most R functions to load data into memory before running the program. It makes the R relatively slower than the other programming language. Because there is a limited amount of data can handle.
On the other hand, SPSS provides faster data management functions, i.e., Sort, aggregate, transpose, and merge the table.
R is not the best programming language for decision making. The reason is that R does not offer many algorithms. And most of its packages can only apply the CART (sorting and regression tree).
And the worst part is that their interface is not so user-friendly. It is why it is overwhelming for users to use R packages for decision-making purposes.
On the other hand, SPSS is one of the best statistical programming languages for decision trees. The reason is that SPSS offers the best among user-friendly and understandable user interfaces.
It is quite easy to use for users and also useful in quick decision making.
R is an open-source programming language. That means you don't have to pay a penny to anyone if you want to use R. You can also collaborate on the R language development phase to make it better for you and other users.
In addition to other developers still doing a great job to continue to add new libraries and updates to R without charging anything. On the other hand, SPSS is not a free product.
You have to pay some subscription fees to use it. You can also use the trial version of SPSS before purchasing the licensed version.
Conclusion (R vs SPSS)
In the end, I would like to say that both R and SPSS are in detail, amazing analytical tools and also offer excellent career options. R is an open-source programming language. So it is easy to learn and materialize.
On the other hand, SPSS is a paid product, and you have to buy it for permanent use. If you are a student of statistics and you are not very aware of data analyses, then you should select the SPSS.
The reason is that SPSS offers the best user interface to do statistical analysis with ease. But if you want to do more data visualization tasks, then you need to select R.
Because R has a wide range of data visualization packages, in addition, R is also the best choice for the analysis of Exploratory data (EDA). In the end, I would suggest you choose the SPSS if you are new to the stats.
On the other hand, if you have enough time to learn R, then you should choose R. Now you can be sure to choose between R vs SPSS.
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