SPSS and Excel are closely related. Both are data manipulation tools designed to control data, store information, analyze data and statistics, create graphs, and more. Of course, each of them is focused on different functions and activities. In this article, we will discover which software is the best for specific functionalities. So, keep reading this SPSS vs Excel article, and find out the answer to this question. Which is best? Excel or SPSS?

SPSS, or Statistical Package for Social Science, is a statistical packaging tool commonly used for data manipulation, data storages, batch processing, and creating standard graphics for more analytical features. It has existed for many years under the SPSS Umbrella now under IBM.

This statistics software helps in the statistical analysis and formulation of data manipulation techniques by using different methods, such as statistical tools and advanced algorithms to support a top-down hypothesis testing approach. SPSS manages all data and every column in one variable.

SPSS also features analytics graphs, allowing you to highlight ranges or data. The software also lets you output graphs in HTML files. In a few words, SPSS is the leader of the statistical packaging tools out there.

Excel is a standard data manipulation application that allows you to extract information and insight from data in various formats. It also allows a user to store data in a tabular format and interact with it in several ways. It’s most used to sort and filter data as well as using mathematical formulas and pivot tables to manipulate the data to create new insights. It is also useful for data entry and creating records. 

With Excel, you can easily import and export data, which allows you to share your data entry with all the members of your team or external users. 

This spreadsheet software is also great as an external database and data analysis software. It’s also helpful in creating reports, data storage, mathematical calculations, and more.

When we compared SPSS to Excel, we noticed major differences between both programs. A huge difference is that SPSS and Excel are used for different purposes, with very few exceptions. Next, let’s check the main differences and similarities between both software.

As SPSS is a not-so-well-known software, its interface does not look familiar or kind. SPSS is the major batch processing software on the market, and the developers haven’t paid attention to details like the interface. This way, it can be a bit difficult and confusing to enter this application.

Excel features a familiar and user-friendly interface as it’s over 30 years old. All readers have already used it, so they know it is intuitive if you already know the basic functions and some mathematics concepts. Besides, the learning curve of Excel is short. You can learn all the necessary functions for most businesses in a matter of hours.

SPSS is a statistical analysis software. Thus, it’s mainly used for statistical calculations and data manipulation as per IBM guidelines. To do this, SPSS has a vast library of machine learning algorithms, open source extensibility, text analysis, and integration with big data in the SPSS sub-areas. 

Its flexibility, scalability, and ease of usage make SPSS available for a wide range of users, even novices. Besides, SPSS, as one of the best statistical packages, is suitable for most projects independent of their size. 

As MS Excel is a great spreadsheet software, this is used for data storing, data computing, and data analysis. You can also use it to display the results of your analysis in real-time graphs, charts, or tables.

However, Excel also features some advanced features like statistics, general mathematical operations, such as Calculus Algebra, and advanced statistics for more complex analytics.

The process of SPSS is built-in statistical functions and interactive batches, which perform memory management in the programming areas. In this sense, all its processes connect to all professional activities and large-scale businesses. SPSS processes manipulate data per IBM guidelines as well as computer science industry standards.

Microsoft Excel stores, processes, and manipulates data to reduce redundancy. This data manipulation tool allows you to store data in cells for a better understanding of what you’re doing. This way, Excel provides an understanding of the file for further analysis and users.  

Furthermore, Excel reveals how to extract info and insight from data in various formats.

As SPSS features special data formats for data scientists and analysts, it includes some more specific sub-areas, such as computation, reasoning, statistical mathematics, statistical algorithms, probabilistic theories, discrete structures, and databases. Many of these uses do not provide exactly a good accessibility or understanding of the subject. For this reason, SPSS was designed for connoisseurs.

In short, Excel is more intuitive than its competitor. Excel can also be used for data science, which is a subset of network ability where knowledge of the info is made by applying different technologies. 

Still, Excel provides a more friendly approach since you can easily insert data in cells organized in columns and rows. Knowing all the right formulas, you can store large-scale sensitive data and generate statistics and results, which you can later display through tables, graphs, and general visualizations.

IBM SPSS Statistics is used mainly in data analytics and data science used by data scientists for statistical tests with formulated operations defined by IBM guidelines. SPSS covers the entire technological field. What’s more, SPSS has managed to strongly enter the field of Health Science.

Excel is part of the computer science subset used to study data through various technologies and methods. Most business and data analysts widely use Excel to facilitate data storage and professional manipulation.

SPSS has a special tool called “SPSS Modeler” to facilitate the modeler stream and data visualization. This tool can manage large data chunks and display them via charts, spreadsheets, and bars. SPSS makes it easy to use transforming variables to highlight data and show descriptive statistics. 

Excel provides the best graphical user interface as well as the ability to utilize visualization techniques and graphics tools. In Excel, you can select the information you want to display and easily create a table with standard graphics. In terms of visualization techniques, Excel provides detailed insight into the usage of computing storage and links and relationships between data.

You can get a subscription plan for SPSS starting at USD$99.00 per user per month. It also allows you to build a package that fits your needs. The latter can be perpetual or term licenses. 

Regarding this Microsoft’s product, you can acquire it by subscribing to the Microsoft 365 service or by purchasing the Microsoft Office suite or its standalone version. As you can see in the image above, the latter option costs USD$159.99. On the other hand, the subscription to the Microsoft 365 service starts at USD$6.99 per user per month.

In comparison to these two alternatives, the best option is to acquire a legit CD Key from a third-party seller, such as RoyalCDKeys. Here you can find several versions of the Microsoft Office suite, from Microsoft Office 2019 Professional Puls Key Retail to Microsoft Office 2021 Pro Plus Key Retail Global. The starting price is around €1,80.

• SPSS is great when you do statistical calculations and data manipulation at high speed and performance.
• SPSS is a statistical tool used on ultra-fast devices and advanced machines, like supercomputers. 
• Real-time usage handling and maintenance of large volumes of consumer data. 
• SPSS is great for performing complex analytics such as cluster analysis, factor analysis, logistic regression, and more.
• This software applies to all technical industries and large-scale companies.
• SPSS works great together with a developing branch of science and technology.

• SPSS can be a little expensive to purchase for students. 
• In treating volume and rows, SPSS is similar to Access, not featuring a great spreadsheet style.

• It has a reduction in data redundancy of the memory system by maintaining and handling large amounts of customer data.
• Excel applies to any type of company, either small or large since owners and employees can use its easy-to-use interface to insert data and calculations.
• It’s capable of displaying data efficiently in tables, graphs, and charts. 
• Excel will treat columns and rows like a relational database. So, integrating and storing data is easier. 
• Excel allows you to store data in multiple formats.

• With Excel, it’s really hard to perform statistical computations. To do this, you need to know complex analysis and advanced concepts to carry out the statistical process. 
• If you don’t know exactly how to perform complex analytics, it may take you a long time to learn how to do it. 
• When you use Excel, it is very likely to make some errors when inserting formulas in spreadsheets. Excel leaves room for human error, broken formulas, lost files, etcetera. 
• When your file is growing progressively, it’s more complex to handle and maintain efficiently.

SPSS vs Excel is a hard choice for statistics students and professionals. We believe that SPSS is the best software out there to provide high-quality graphics for analytical features. In this way, SPSS is the king of the statistical world. 

Conversely, Excel, like no other statistics software, allows you to create custom functions for your mathematical calculations and more. 

If you have a big business and want to understand your organization's statistics, then SPSS is your choice since it’s a tool formulated for data analysis. 

Instead, if you want to perform simpler mathematical operations, or any data study, then Excel is the program for you.

Since both software offers you a free trial period, you can taste them and draw your conclusions.