Comparing SPSS vs Excel

Data Analysis, Excel VS SPSS Statistics
Comparing SPSS vs Excel
An important question occurs to many of people interested in the field of data analysis or people who may need to use data analysis programs either for work or research; “What is the difference between Excel and SPSS? And when is each of them recommended?”.

In this article we provide a brief description of the advantages and disadvantages, this description is categorized according to the specialization or field of the required data analysis:

First: data analysis for academic research

We absolutely recommend using SPSS, as it offers very wide statistical analyses that has endless options. In this field, Excel cannot in any way provide what SPSS does.

For example, SPSS provides:

Parametric and non-parametric tests with wide options that include many tests required for researchers who are not specialized in statistics.
Regression and correlation analysis of its various types, linear and non-linear, with tests for them and analysis options that are widely related to them.
Time series analysis.
Questionnaire reliability tests.
Neural networks analysis.
Factorial analysis.
Survival analysis.
Statistical quality control analysis and charts.

Along with many other statistical analyses that serve academic fields.

Second: data analysis for non-academic research

It can be classified into several levels of data analysis:

Descriptive data analysis:
Comparing SPSS vs Excel
In general, the two programs are able to provide all the analyses required in descriptive statistical analysis, but Excel contains some minor flaws, such as that it does not arrange the answers according to their logical order, but rather in an alphabetical order, and it can’t provide calculations related to questions that include texts in addition to calculations related to their own order (Ordinal data) such as calculating the Likert Scale.

SPSS is characterized by providing tools for analyzing multi-select questions and with advanced options, which Excel does not provide, therefore, we need to use functions to get those analyses which options are limited with problems with the percentage that we get from it.

Disaggregation analysis:

It can be said that both programs are reliable in this aspect, except in the case of multiple and complex disaggregation/cross-tabulation with multi-select questions, in these cases, Excel becomes slower and less effective, while SPSS offers all options, no matter how complex they are, at the same speed required for descriptive statistical analysis and simple disaggregation. In addition to aforementioned, there are features such as filtering and data splitting features provided by SPSS, which accelerate data analysis to a very big scale, as it is possible to analyze the required data for 20 regions separately to be done at the same speed of analyzing data for one region, while in Excel, this means doing 20 times the work.

SPSS provides the features of descriptive analysis and data disaggregation much faster than we may think, as some analyses that take a week using Excel can be completed in just a few minutes using SPSS.

Third: Analyzing data of demographic indicators

When talking about demographic indicators, we find a challenge facing each of these two programs. In SPSS, we can perform numerous, complex and very fast arithmetic operations that outperform Excel, however, SPSS has some minor weaknesses that are important at the same time; among the most important matters that have been noticed in this regard is conducting multi-column conditional arithmetic operations, as SPSS provides multi-column arithmetic operations, but these operations do not contain multiple conditions, on the other hand, Excel provides this feature with a wide variety of conditional and effective functions.

Fourth: Data management and linking databases in the analysis

In this particular aspect, we find the clear distinction of Excel, as with the Power Query package, it offers features of data management, merging, and the possibility for aggregation and cleaning the data, in addition to the ability to link various databases without merging them, and analyzing them together with all types of analyses.

As for SPSS program, it does not include the feature of analyzing isolated databases without the need to merge them, on the other hand, it can solve a large part of this problem by merging databases, but this entails many challenges and great possibilities for error. When merging more than one database, there is usually a repetition of cases to match the other database, and this means that when we analyze the database that has been duplicated, we must perform operations that cancel this repetition in order to obtain correct analyses.

The features of data management and analyzing isolated databases together is considered as a great advantage of Excel, but in most cases it is not required, as it is only needed in complex and advanced projects.
Comparing SPSS vs Excel
On the other hand, SPSS program in the Data menu provides many features that can only be described as great, and the lines of this article are insufficient to talk about them, but they can be briefly described by saying that they gives data management some features that can outperform Excel in some aspects, such as the Unpivot or Restructure features that SPSS provides including features that are far more advanced and powerful than Excel.

Fifth: Weighting

One of the very important aspects of data analysis, especially with regard to demographic statistics, humanitarian needs analysis and advanced market research, is the Weighting feature, which helps to calculate the data after taking into account a weight that expresses, for example, the population of the governorate or the studied area, which gives it an amount of needs that is commensurate with its size.

This feature is not provided by Excel, if we wanted to calculate the weights manually using functions in it, this sometimes causes problems in the results, especially in the disaggregation analyses.

In SPSS, once you choose the option of Calculating Weights, it will be automatically applied to all calculations whatever they are, even on charts, and we can stop calculating weights with only one click.

This is a simple comparison between the two programs, we hope this comparison gives a preliminary perspective and help data analysis specialists and institutions that need to build the capacities of their team in this field to choose the most suitable program for them.

By:
Ghaith Albahr: CEO of INDICATORS