IBM SPSS Statistics Base - Essential tools for statistical analysis

IBM SPSS Statistics Base is statistical analysis software that delivers the core capabilities you need to take the analytical process from start to finish. It is easy to use and includes a broad range of procedures and techniques to help you increase revenue, outperform competitors, conduct research and make better decisions.

SPSS Statistics Base provides essential statistical analysis tools for every step of the analytical process.  

  • A comprehensive range of statistical procedures for conducting accurate analysis.
  • Built-in techniques to prepare data for analysis quickly and easily.
  • Sophisticated reporting functionality for highly effective chart creation.
  • Powerful visualization capabilities that clearly show the significance of your findings.
  • Support for all types of data including very large data sets.


IBM SPSS Advanced Statistics - Powerful modeling techniques for analyzing complex relationships

IBM SPSS Advanced Statistics provides univariate and multivariate modeling techniques to help users reach the most accurate conclusions when working with data describing complex relationships. These sophisticated analytical techniques are frequently applied to gain deeper insights from data used in disciplines such as medical research, manufacturing, pharmaceuticals and market research.

SPSS Advanced Statistics provides the following capabilities:

  • General linear models (GLM) and mixed models procedures.
  • Generalized linear models (GENLIN) including widely used statistical models, such as linear regression for normally distributed responses, logistic models for binary data and loglinear models for count data.
  • Linear mixed models, also known as hierarchical linear models (HLM), which expands the general linear models used in the GLM procedure so that you can analyze data that exhibit correlation and non-constant variability.
  • Generalized estimating equations (GEE) procedures that extend generalized linear models to accommodate correlated longitudinal data and clustered data.
  • Generalized linear mixed models (GLMM) for use with hierarchical data and a wide range of outcomes, including ordinal values.
  • Survival analysis procedures for examining lifetime or duration data.


IBM SPSS Bootstrapping - Create More Reliable Models and Generate More Accurate Results

IBM SPSS Bootstrapping makes it simple to test the stability and reliability of your models so that they produce accurate, reliable results.

Whether you conduct academic or scientific research, study issues in the public sector or provide the analyses that support business decisions, it's important that your models are stable. Test model stability quickly and easily with IBM SPSS Bootstrapping.

IBM SPSS Bootstrapping provides an efficient way to ensure that your models are stable and reliable, so your analysis generates more accurate results. With IBM SPSS Bootstrapping, you can:

  • Quickly and easily estimate the sampling distribution of an estimator by re-sampling with replacement from the original sample
  • Estimate the standard errors and confidence intervals of a population parameter such as the mean, median, proportion, odds ratio, correlation coefficient, regression coefficient, and numerous others
  • Create thousands of alternate versions of your dataset for more accurate analysis


IBM SPSS Categories - Predict outcomes and reveal relationships in categorical data

IBM SPSS Categories provides you with all the tools you need to obtain clear insight into complex categorical and numeric data, as well as high-dimensional data.

Use IBM SPSS Categories to understand which characteristics consumers relate most closely to your brand, or to determine customer perception of your products compared to other products you or your competitors offer.

  • Discover underlying relationships through perceptual maps, bi plots and tri plots
  • Work with and understand nominal (e.g. salary) and ordinal (e.g. education level) data with procedures similar to conventional regression, principal components and canonical correlation to predict outcomes and reveal relationships
  • Visually interpret datasets and see how rows and columns relate in large tables of scores, counts, ratings, rankings or similarities
  • Deal with non-normal residuals in numeric data or nonlinear relationships between predictor variables (e.g. customer or product attributes) and the outcome variable (e.g. purchase/non-purchase)
  • Use Ridge Regression, the Lasso, the Elastic Net, variable selection and model selection for both numeric and categorical data


IBM SPSS Complex Samples - Correctly and easily compute statistics for complex sampling

IBM SPSS Complex Samples helps make more statistically valid inferences by incorporating the sample design into survey analysis.

IBM SPSS Complex Samples provides the specialized planning tools and statistics you need when working with complex sample designs, such as stratified, clustered or multistage sampling.

This module of IBM SPSS Statistics is an indispensable for survey and market researchers, public opinion researchers or social scientists seeking to reach more accurate conclusions when working with sample survey methodology. You can more accurately work with numerical and categorical outcomes in complex sample designs using two algorithms for analysis and prediction. In addition, you can use this module’s techniques to predict time to an event.


IBM SPSS Conjoint - Easily Discover What People Value

IBM SPSS Conjoint gives you a realistic way to measure how individual product attributes affect people’s preferences.

With IBM SPSS Conjoint, you can easily measure the tradeoff effect of each product attribute in the context of a set of product attributes – as consumers do when making purchasing decisions.

For example, you can answer critical product market research questions:

  • What product attributes do my customers care about?
  • What are the most preferred attribute levels?
  • How can I most effectively perform pricing and brand equity studies?

You can answer all of your questions before you spend valuable resources trying to bring products or services to market. Use IBM SPSS Conjoint to focus your efforts on the service or product development that has the best chance of succeeding.

IBM SPSS Conjoint gives you all the tools you need for developing product and service attribute ratings. You can use its three procedures to:

  • Generate designs easily – use Orthoplan, the design generator, to produce an orthogonal array of alternative potential products or services that combine different product/service features at specified levels
  • Print "cards" to elicit respondents' preferences – use Plancards to quickly generate cards that respondents can sort to rank alternative products
  • Get informative results – analyze your data using Conjoint, a procedure that's a specially tailored version of regression. Find out which product/service attributes are important and at which levels they are most preferred. You can also perform simulations that tell you the market share of preference for alternative products.


IBM SPSS Custom Tables - Easily analyze and communicate your analytical results

IBM SPSS Custom Tables helps you easily understand your data and quickly summarize your results in different styles for different audiences.

More than a simple reporting tool, IBM SPSS Custom Tables combines comprehensive analytical capabilities with interactive table-building features to help you learn from your data and communicate the results of your analyses as professional-looking tables that are easy to read and interpret.

  • Compare means or proportions for demographic groups, customer segments, time periods or other categorical variables when you include inferential statistics
  • Select summary statistics - from simple counts for categorical variables to measures of dispersion - and sort categories by any summary statistic used
  • Choose from three significance tests: Chi-square test of independence, comparison of column means (t test), or comparison of column proportions (z test)
  • Drag and drop variables onto the interactive table builder to create results as pivot tables
  • Preview tables in real time and modify them as you create them
  •  Exclude specific categories, display missing value cells and add subtotals to your tables
  • Export tables to Microsoft® Word, Excel®, PowerPoint® or HTML for use in reports


IBM SPSS Data Preparation - Improve Data Preparation for More Accurate Results

IBM SPSS Data Preparation gives analysts advanced techniques to streamline the data preparation stage of the analytical process. IBM SPSS Statistics Base, IBM SPSS Data Preparation provides specialized techniques to prepare your data for more accurate analyses and results.

With IBM SPSS Data Preparation, you can:

  • Quickly identify suspicious or invalid cases, variables and data values
  • View patterns of missing data
  • Summarize variable distributions
  • Optimally bin nominal data
  • More accurately prepare your data for analysis
  • Use Automated Data Preparation (ADP) to detect and correct quality errors and impute missing values in one efficient step
  • Get recommendations and visualizations to help you determine which data to use


IBM SPSS Decision Trees - Easily identify groups and predict outcomes

The IBM SPSS Decision Trees module helps you better identify groups, discover relationships between them and predict future events.

This module features highly visual classification and decision trees. These trees enable you to present categorical results in an intuitive manner, so you can more clearly explain categorical analysis to non-technical audiences.

IBM SPSS Decision Trees enables you to explore results and visually determine how your model flows. This helps you find specific subgroups and relationships that you might not uncover using more traditional statistics. The module includes four established tree-growing algorithms.

Use IBM SPSS Decision Trees if you need to identify groups and sub-groups. Applications include:

  • Database marketing
  • Market research
  • Credit risk scoring
  • Program targeting
  • Marketing in the public sector


IBM SPSS Direct Marketing - The analytical toolkit marketers need to easily identify the right customers and improve campaign results.

IBM SPSS Direct Marketing helps you understand your customers in greater depth, improve your marketing campaigns and maximize the ROI of your marketing budget.

Conduct sophisticated analyses of your customers or contacts easily – and with a high level of confidence in your results. Choose from recency, frequency and monetary value (RFM) analysis, cluster analysis, prospect profiling, postal code analysis, propensity scoring and control package testing. The software’s intuitive interface enables you to:

  • Identify which customers are likely to respond to specific promotional offers
  • Develop a marketing strategy for each customer group
  •  Compare the effectiveness of direct mail campaigns
  • Boost profits and reduce costs by mailing only to those customers most likely to respond
  • Prevent spam complaints by monitoring the frequency of e-mails sent to each customer group
  • Select potential business locations
  • Connect to Salesforce.com to extract customer information, collect details on opportunities and perform analyses


IBM SPSS Exact Tests - More Accurately Analyze Small Datasets or Those with Rare Occurrences

IBM SPSS Exact Tests gives you what's needed to more accurately work with small samples and analyze rare occurrences in large datasets.

IBM SPSS Exact Tests enables you to use small samples and still feel confident about the results. With the money saved using smaller sample sizes, you can conduct surveys or test direct marketing programs more often. Stay ahead of the competition by using these resources to find new opportunities.

Easily Interpret and Apply Exact Tests

IBM SPSS Exact Tests is easy to use. You can perform a test any time, with just a click of a button – during your original analysis or when you rerun it. With IBM SPSS Exact Tests, there is no steep learning curve, because you don't need to learn any new statistical theories or procedures. You simply interpret the exact tests results the same way you already interpret the results in IBM SPSS Statistics Base.

You'll always have the right statistical test for your data situation. IBM SPSS Exact Tests provides more than 30 exact tests, which cover the entire spectrum of nonparametric and categorical data problems for small or large datasets. These tests include one-sample, two-sample and K-sample tests on independent or related samples, goodness-of-fit tests, tests of independence in RxC contingency tables and on measures of association.


IBM SPSS Forecasting - Build Expert Time-series Forecasts -- in a Flash

IBM SPSS Forecasting enables analysts to predict trends and develop forecasts quickly and easily -- without being an expert statistician.

Reliable forecasts can have a major impact on your organization’s ability to develop and implement successful strategies. Unlike spreadsheet programs, IBM SPSS Forecasting has the advanced statistical techniques needed to work with time-series data regardless of your level of expertise.

  • Analyze historical data and predict trends faster, and deliver information in ways that your organization’s decision makers can understand and use
  • Automatically determine the best-fitting ARIMA or exponential smoothing model to analyze your historic data
  • Model hundreds of different time series at once, rather than having to run the procedure for one variable at a time
  • Save models to a central file so that forecasts can be updated when data changes, without having to re-set parameters or re-estimate models
  • Write scripts so that models can be updated with new data automatically


IBM SPSS Missing Values - Build Better Models When You Estimate Missing Data

IBM SPSS Missing Values is used by survey researchers, social scientists, data miners, market researchers and others to validate data.

Missing data can seriously affect your models – and your results. Ignoring missing data, or assuming that excluding missing data is sufficient, risks reaching invalid and insignificant results. To ensure that you take missing values into account, make IBM SPSS Missing Values part of your data management and preparation.

  • Uncover Missing Data Patterns
  • Easily examine data from several different angles using one of six diagnostic reports, then estimate summary statistics and impute missing values
  • Quickly diagnose serious missing data imputation problems
  • Replace missing values with estimates
  • Display a snapshot of each type of missing value and any extreme values for each case
  • Remove hidden bias by replacing missing values with estimates to include all groups ¬– even those with poor responsiveness


IBM SPSS Neural Networks - Find More Complex Relationships in Your Data

IBM SPSS Neural Networks offers non-linear data modeling procedures that enable you to discover more complex relationships in your data.

Using the procedures in IBM SPSS Neural Networks, you can develop more accurate and effective predictive models. The result? Deeper insight and better decision making.

What is a neural network?

A computational neural network is a set of non-linear data modeling tools consisting of input and output layers plus one or two hidden layers. The connections between neurons in each layer have associated weights, which are iteratively adjusted by the training algorithm to minimize error and provide accurate predictions.

Complement traditional statistical techniques

The procedures in IBM SPSS Neural Networks complement the more traditional statistics in IBM SPSS Statistics Base and its modules. Find new associations in your data with Neural Networks and then confirm their significance with traditional statistical techniques.


IBM SPSS Regression - Improve Predictions with Powerful Nonlinear Regression Software

IBM SPSS Regression enables you to predict categorical outcomes and apply a wide range of nonlinear regression procedures.

You can apply IBM SPSS Regression to many business and analysis projects where ordinary regression techniques are limiting or inappropriate: for example, studying consumer buying habits or responses to treatments, measuring academic achievement, and analyzing credit risks.

IBM SPSS Regression includes the following procedures:

  • Multinomial logistic regression: Predict categorical outcomes with more than two categories
  • Binary logistic regression: Easily classify your data into two groups
  • Nonlinear regression and constrained nonlinear regression (CNLR): Estimate parameters of nonlinear models
  • Weighted least squares: Gives more weight to measurements within a series
  • Two-stage least squares: Helps control for correlations between predictor variables and error terms
  • Probit analysis: Evaluate the value of stimuli using a logit or probit transformation of the proportion responding