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IBM SPSS Statistics

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What is IBM SPSS Statistics?

SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).

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Categories & Use Cases

Media

Screenshot of SPSS Statistics Forecasting. This enables users to build time-series forecasts regardless of their skill level.
Screenshot of SPSS Statistics Regression. These predict categorical outcomes and apply nonlinear regression procedures.
Screenshot of IBM SPSS Statistics Neural Networks. These can discover complex relationships and improve predictive models.
Screenshot of IBM SPSS Statistics Curated Help. These can interpret correlation output.
Screenshot of IBM SPSS Statistics AI Output Assistant interprets statistical output in easy to consume language

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Screenshot of SPSS Statistics Forecasting. This enables users to build time-series forecasts regardless of their skill level.

Who Buys & Uses IBM SPSS Statistics

IBM SPSS Statistics Reviews

What users are saying about IBM SPSS Statistics.
View all IBM SPSS Statistics reviews

Pros

  • Intuitive graphical user interface and ease of use for complex statistical tasks
  • Robust data preparation and management features for cleaning and organizing datasets
  • Comprehensive statistical analysis capabilities, including regression and descriptive statistics

Cons

  • High pricing and licensing costs are considered prohibitive for some organizations
  • User interface requires modernization to align with contemporary design standards
  • Difficulties with data transfer and integration, specifically copy-paste functionality

Comprehensive and Accurate Statistical Analysis App

Pevangelista Massimo Ferrantini
National Sales And Marketing Director in Marketing at Hub Legno (1-10 employees)

Use Cases and Deployment Scope

IBM SPSS has effectively helped our company in transforming raw data to actionable and meaningful insights.
We use IBM SPSS to conduct employee and customer surveys, predictive analytics and this guides us in generating reliable reports.
The program has comprehensive statistical measures that guides both non technical and technical users on data analysis
We get visualized results based on the analysis done, which assist us in decision making.

Pros

  • Complex and large datasets are effectively analyzed by this tool
  • All sophisticated analysis are automated and this uses hypothesis testing and regression analysis and
  • The transformation of raw data to actionable insights is a brilliant feature from the app

Cons

  • IBM SPSS has some add on modules that are expensive
  • Beginners find the interface more technical and some procedures are steep to learn
  • The customization part is problematic and needs some administrative intervention

Return on Investment

  • The automation of advanced statistical analysis reduces errors that can affect the decisions we make
  • The generation of actionable insights guides the company in proper planning
  • The optimization of customer satisfaction surveys helps us in determining what customers beed

A Masterful and Top-ranking Statistical Analysis Tool.

Incentivized
Babulal Choudhary
Data Analyst Manager in Research & Development at Brossard App Design (11-50 employees)

Use Cases and Deployment Scope

IBM SPSS Statistics enables me to analyze and manage large volumes of data more effectively. IBM SPSS Statistics is also a very useful tool for simplifying data entry. I'm delighted with IBM SPSS Statistics because it allows me to import/collect data from various sources.

Pros

  • Accurate forecasts.
  • Data import.
  • Advanced statistical analysis.
  • Data preparation.
  • Data visualization.
  • Customizable dashboards and reports.
  • Predictive analytics and modeling.
  • Data entries.

Cons

  • IBM SPSS Statistics delivers excellent performance and results in statistical analysis, so no challenges were encountered.

Return on Investment

  • IBM SPSS Statistics saves time and energy by automating and simplifying the manual data processing process.
  • IBM SPSS Statistics doesn't require much programming knowledge.
  • IBM SPSS Statistics delivers accurate data results.
  • Unlocking of valuable data insights.

Other Software Used

FME, Tableau Desktop, Xero

IBM SPSS Statistics for more than 20 years

Incentivized
Dr. Mohammad Reza HabibiView profile
Professor of Marketing in Marketing at California State University (1001-5000 employees)

Use Cases and Deployment Scope

I am researcher and instructor. I have been using IBM SPSS Statistics for a long time for over 20 years. From simple frequency charts, data manipulation and trimming, to more sophisticated regressions based analytics, I have been using IBM SPSS Statistics and also teaching it to new generations. It does support all of my needs.

Pros

  • Data Cleaning and missing data treatments
  • Charts and visualizations
  • Regression analytics
  • Structural Equation Modeling
  • ANOVA and MANOVA

Cons

  • Easier and more automated data transfer and variable naming and labeling

Return on Investment

  • Accuracy
  • time saving
  • high quality visualizations

Alternatives Considered

Microsoft Excel

SPSS - The Best Data Analytics Tool.

Incentivized
Verified User
Analyst in Marketing (1001-5000 employees)

Use Cases and Deployment Scope

We use IBM SPSS Statistics to analyze large-scale datasets with thousands of entries. We use a variety of features within SPSS to uncover insights from these datasets, including descriptive statistics, frequencies, crosstabs, significance testing, and predictive modeling. The main business problems we help solve by using SPSS include uncovering consumer insights related to our company's products, such as which products are most useful, which products do consumers still need, and how we can improve our product offerings to reach more consumers.

Pros

  • Handling large datasets.
  • User-friendly menu system.
  • Significance testing.
  • Data analysis.
  • Thorough data outputs.

Cons

  • Some legacy tests are hard to find in menus, often buried under 3-4 submenus before I can find what I'm looking for.
  • Default data visualizations (i.e., charts and graphs) are very basic compared to other data visualization tools.
  • The copy-and-paste feature between data sets or between Excel files and SPSS files does not always work, sometimes causing friction when trying to amend data.

Return on Investment

  • Time savings when it comes to significance testing.
  • Increased uptime by handling multiple large-scale datasets at once rather than one at a time.
  • Improved project management by completing data analyses faster and more efficiently.

Alternatives Considered

Microsoft Excel

Other Software Used

Microsoft Excel, Tableau Desktop, Microsoft Powerpoint

A Reliable Data Tool

Incentivized
Verified User
Employee in Marketing (10,001+ employees)

Use Cases and Deployment Scope

It was used to analyze research, some survey data, and look deeper into student outcomes. It helped us address data analysis needs for academic research, university accreditation, and program evaluation. Some use case scenarios include statistical analysis for faculty research, student projects, and institutional reporting.

Pros

  • User interface simple and easy to use
  • Great for analyzing survey data
  • Makes task straighforward

Cons

  • Better intergration
  • Cloud based sharing could be improved

Return on Investment

  • Saved a lot of time

IBM SPSS Statistics Alternatives

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