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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Statistics

    Score8 out of 10
    N/ASPSS 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).

    $105

    per month per user

    Jupyter Notebook

    Score8.6 out of 10
    N/AJupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
    Pricing
    IBM SPSS StatisticsJupyter Notebook
    Editions & Modules
    Base
    USD 3,830
    one-time fee per user
    Standard
    USD 8,440
    one-time fee per user
    Professional
    USD 16,900
    one-time fee per user
    Premium
    USD 25,200
    one-time fee per user
    Monthly subscription
    USD 105
    per month per user
    Annual subscription
    USD 1,188.00
    per year per user
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM SPSS StatisticsJupyter Notebook
    Free Trial
    YesNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    IBM SPSS StatisticsJupyter Notebook
    Considered Both Products
    IBM
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    94%
    Would buy again
    49 Answers
    100%
    Would buy again
    23 Answers
    Delivers good value for the price
    91%
    Delivers good value for the price
    42 Answers
    100%
    Delivers good value for the price
    23 Answers
    Happy with the feature set
    98%
    Happy with the feature set
    51 Answers
    96%
    Happy with the feature set
    22 Answers
    Lived up to sales and marketing promises
    97%
    Lived up to sales and marketing promises
    34 Answers
    100%
    Lived up to sales and marketing promises
    17 Answers
    Implementation went as expected
    97%
    Implementation went as expected
    35 Answers
    95%
    Implementation went as expected
    20 Answers
    Features
    IBM SPSS StatisticsJupyter Notebook
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM SPSS Statistics and Jupyter Notebook
    Feature
    IBM SPSS Statistics
    -
    Ratings
    Jupyter Notebook
    9.0
    22 Ratings
    7% above category average
    Connect to Multiple Data Sources00 Ratings10.022 Ratings
    Extend Existing Data Sources00 Ratings10.021 Ratings
    Automatic Data Format Detection00 Ratings8.514 Ratings
    MDM Integration00 Ratings7.415 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM SPSS Statistics and Jupyter Notebook
    Feature
    IBM SPSS Statistics
    -
    Ratings
    Jupyter Notebook
    7.0
    22 Ratings
    18% below category average
    Visualization00 Ratings6.022 Ratings
    Interactive Data Analysis00 Ratings8.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM SPSS Statistics and Jupyter Notebook
    Feature
    IBM SPSS Statistics
    -
    Ratings
    Jupyter Notebook
    9.5
    22 Ratings
    15% above category average
    Interactive Data Cleaning and Enrichment00 Ratings10.021 Ratings
    Data Transformations00 Ratings10.022 Ratings
    Data Encryption00 Ratings8.514 Ratings
    Built-in Processors00 Ratings9.314 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM SPSS Statistics and Jupyter Notebook
    Feature
    IBM SPSS Statistics
    -
    Ratings
    Jupyter Notebook
    9.3
    22 Ratings
    10% above category average
    Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
    Automated Machine Learning00 Ratings9.218 Ratings
    Single platform for multiple model development00 Ratings10.022 Ratings
    Self-Service Model Delivery00 Ratings8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM SPSS Statistics and Jupyter Notebook
    Feature
    IBM SPSS Statistics
    -
    Ratings
    Jupyter Notebook
    10.0
    20 Ratings
    15% above category average
    Flexible Model Publishing Options00 Ratings10.020 Ratings
    Security, Governance, and Cost Controls00 Ratings10.019 Ratings
    Best Alternatives
    IBM SPSS StatisticsJupyter Notebook
    Small Businesses
    No answers on this topic
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Alteryx Platform
    Score9 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    Alteryx Platform
    Score9 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS StatisticsJupyter Notebook
    Likelihood to Recommend
    8.5
    (116 ratings)
    10.0
    (23 ratings)
    Likelihood to Renew
    8.5
    (23 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (15 ratings)
    10.0
    (2 ratings)
    Availability
    6.0
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    6.4
    (12 ratings)
    9.0
    (1 ratings)
    Implementation Rating
    8.7
    (7 ratings)
    -
    (0 ratings)
    Configurability
    5.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    5.0
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    5.0
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    5.0
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    5.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM SPSS StatisticsJupyter Notebook
    Likelihood to Recommend
    IBM
    IBM SPSS Statistics is well suited for pretty much any data analytic scenario. It can handle extremely complex and large-scale datasets with ease. It especially shines if you have to do any kind of analyses that involve significance testing. Being able to do any number of significance tests (i.e., t-tests, chi-square, ANOVAs, etc.) right inside the tool is very valuable. The only scenario I would say it is less appropriate is if you need to work on a very small dataset and answer very simple questions, like frequencies or averages. In those cases, something like Excel could probably do the job just as easily.
    Incentivized
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    Open Source
    I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
    Incentivized
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    Pros
    IBM
    • SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
    • Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
    • SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
    • SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
    • In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
    Incentivized
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    Open Source
    • Simple and elegant code writing ability. Easier to understand the code that way.
    • The ability to see the output after each step.
    • The ability to use ton of library functions in Python.
    • Easy-user friendly interface.
    Incentivized
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    Cons
    IBM
    • Cost is becoming prohibitive.
    • Availability of procedures in the base package seems to be dwindling.
    • The copy-and-paste function from output to Excel is not as easy as it once was (now I have to do a "paste special").
    • Text and date handling are terrible.
    • Need to include AI-based NLP for survey verbatims and other text-based fields. This is becoming increasingly important in the CX world, yet SPSS seems to be ignoring it.
    Incentivized
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    Open Source
    • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
    • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    Both
    money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
    using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
    entry and data analysis for my research. Output from SPSS is very easy to
    interpret for data analysis and findings
    Incentivized
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    Open Source
    No answers on this topic
    Usability
    IBM
    Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
    Incentivized
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    Open Source
    Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
    Incentivized
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    Reliability and Availability
    IBM
    SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data
    Incentivized
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    Open Source
    No answers on this topic
    Performance
    IBM
    SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.
    Incentivized
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    Open Source
    No answers on this topic
    Support Rating
    IBM
    I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
    Read full review
    Open Source
    I haven't had a need to contact support. However, all required help is out there in public forums.
    Incentivized
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    Implementation Rating
    IBM
    Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
    Incentivized
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    Open Source
    No answers on this topic
    Alternatives Considered
    IBM
    If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.
    Incentivized
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    Open Source
    With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
    Incentivized
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    Scalability
    IBM
    I am neutral because I have not had to look into scalability since I am using as a student.
    Incentivized
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    Open Source
    No answers on this topic
    Return on Investment
    IBM
    • I found SPSS easier to use than SAS as it's more intuitive to me.
    • The learning curve to use SPSS is less compared to SAS.
    • I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
    Incentivized
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    Open Source
    • Positive impact: flexible implementation on any OS, for many common software languages
    • Positive impact: straightforward duplication for adaptation of workflows for other projects
    • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
    Incentivized
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    ScreenShots

    IBM SPSS Statistics Screenshots

    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