This webinar gives an introduction to some of the ways in which SPSS Modeler can help organisations to make sense of their customer survey and feedback data, including free text fields and other unstructured data.
Analytics for customer surveys and feedback Read More »
This webinar presents different applications of predictive analytics for database marketers. The aim is to help organisations understand how they can use the information in their marketing database to more effectively acquire new customers as well as to retain those they already have and maximise their value to the organisation.
Predictive analytics for database marketing using SPSS Modeler Read More »
This webinar provides an introduction to the CRISP-DM methodology and discussed how best to manage each stage of the process in order to maximise your chances of success.
An introduction to CRISP DM Read More »
Around 20% of students do not complete their studies, making retention a big concern for all universities and HEIs. Watch this webinar to understand which student characteristics and behaviours most influence the chances of them remaining engaged with their course.
Using advanced analytics to improve student retention Read More »
This webinar gives a brief introduction to predictive analytics, how it differs from business intelligence, and suggests ways in which organisations can get started with predictive analytics quickly and easily.
An introduction to predictive analytics in just one hour Read More »
IBM is about to release the latest version of SPSS Statistics. Here’s a summary of some of the new enhancements
What’s new in SPSS v28? Read More »
Correlation is a term that we employ in everyday speech to denote things that appear to have a mutual relationship.
What is correlation and when is it useful? Read More »
The chi-squared test is used to examine differences with between fields with different categories and to determine whether those differences are significant.
What is a Chi Square test and when would you use it? Read More »
The real world, whether it be the physical world, for example machines, or the natural world, for example human and
What is the difference between the various types of statistical models? Read More »
When you’re conducting any kind of statistical analysis, it’s vital that you select the correct tests to perform, given the
How do I choose the correct statistical test? Read More »
IBM SPSS Advanced Analytical Products, including IBM SPSS Statistics and IBM SPSS Modeler, can be implemented and licensed in different ways.
What’s the difference between the various SPSS license types? Read More »
In order for Smart Vision Europe Ltd to be able to assist you with the transfer of an SPSS license
How do I transfer my SPSS license to another machine? Read More »
You can easily change language from English to another language of your choice directly within SPSS Statistics. This can be
How do I change the language in SPSS? Read More »
When your licence comes to an end you will need to buy a licences, you do not need to reinstall
How do I update my SPSS activation code? Read More »
Sometimes it can be useful to know which SPSS modules you have installed and are licensed for. There’s a simple
How do I know which SPSS modules I have installed? Read More »
In these videos Jarlath Quinn introduces the concept of Structural Equation Modelling with SPSS AMOS. In the first video Jarlath uses the example of creating a simple linear model to illustrate the functionality in the AMOS interface.
Introduction to structural equation modelling with SPSS Amos – part one Read More »
In these videos Jarlath Quinn introduces the concept of Structural Equation Modelling with SPSS AMOS. In the second video Jarlath shows how to perform a basic Confirmatory Factor Analysis in AMOS.
Introduction to structural equation modelling with SPSS Amos – part two Read More »
Bootstrap aggregation, also called bagging, is a random ensemble method designed to increase the stability and accuracy of models. It involves creating a series of models from the same training data set by randomly sampling with replacement the data.
6 secrets of building better models part one: bootstrap aggregation Read More »
Boosting is another ensemble model-building method that was designed to help develop strong classification models from weak classifiers. Boosting methods focus on error (or misclassifications) that occur in prediction.
6 secrets of building better models part two: boosting Read More »
Feature Engineering is really just a fancy term for creating new data. Very often we can help an algorithm build better models by preparing the input data in a way that allows it to detect a clearer signal in the often noisy data. In machine learning variables are often referred to as ‘features’, so feature engineering refers to the transformation of variables or the creation of new ones.
6 secrets of building better models part three: feature engineering Read More »
Ensemble modelling refers to the practice of combining the predictions of separate models on the old principle that “two heads are better than one”. Ensemble methods can be particularly effective when combining models that have been created using completely different algorithms.
6 secrets of building better models part four: ensemble modelling Read More »
The idea of meta modelling is to build a predictive model using the predictions or scores generated by another model. By adding the predictive scores generated by an initial modelling algorithm to an existing pool of predictor fields, a second algorithm can then exploit these scores in to build a final more accurate model.
6 secrets of building better models part five: meta models Read More »
Split models or split population modelling is another technique that allows the user to build multiple models which can then be combined to create a single prediction. The idea with split modelling is that if the data represent different populations or contain separate groups that behave in very different ways, assuming that a single model can explain all the inherent variability across these distinct populations might be unreasonable.
6 secrets of building better models part six: split models Read More »
In this video Jarlath Quinn takes a first look at SPSS Modeler v18.2 and demonstrates some of the new functionality that’s included within this release.
A first look at SPSS Modeler v18.2 Read More »
We’re often asked how you can change the appearance of the tables that SPSS generates as output. In this video Jarlath Quinn demonstrates two different ways to do this, either by choosing a different table look in the edit / options function, or by editing the table properties directly yourself.
How to change the appearance of your output in SPSS Statistics Read More »
In this video Jarlath Quinn demonstrates how to merge data files within SPSS Statistics using each of the two main methods, either adding cases (combining files with the same fields but additional rows) or adding variables (combining files by joining variables to a target file using something like an ID field as a ‘keyed variable’).
How to merge files in SPSS Statistics Read More »
SPSS users often want to be able to create grouped or banded data from continuous fields such as, for example, creating age groups or income bands from continuous fields. In this video Jarlath Quinn demonstrates how to use the visual binning procedure within SPSS Statistics to do this.
How to create grouped or banded variables in SPSS Statistics Read More »
Recoding your data means changing the values of a variable so that they represent something else. Within SPSS Statistics there is more than one type of recode that can be performed.
How to recode your data in SPSS Statistics Read More »
In this video Jarlath Quinn demonstrates how to use the functions within the explore command in SPSS Statistics to test for normality.
How to check your data for normality in SPSS Statistics Read More »
In this video Jarlath Quinn demonstrates how to work with date and time variables in SPSS using the SPSS date and time wizard.
How to calculate with dates in SPSS Statistics Read More »
In this video Jarlath Quinn demonstrates how to use SPSS Statistics to define data filters in order to select particular cases for analysis. This can be done either to create a temporary selection or to create a permanent new file with only a subsection of cases included within it.
How to select cases in SPSS Statistics Read More »
In this video Jarlath Quinn demonstrates how to reverse the values of a rating scale (such as an agreement scale or a satisfaction scale) in SPSS Statistics, so that the highest value becomes the lowest value and vice versa.
How to reverse a scale in SPSS Statistics Read More »
SPSS users often want to know how they can combine variables together. In this video Jarlath Quinn demonstrates how to use the compute procedure to calculate the mean of a number of variables to create one combined variable, and also how to use the count values procedure to count how many times a particular value occurs across a series of variables in order to create an overall count.
How to combine variables in SPSS Statistics Read More »
In this video Jarlath Quinn introduces the popular TURF analysis technique and demonstrates how to apply it in IBM SPSS Statistics. TURF analysis is used in many industries to find the optimal sub-group of options from a wider portfolio in order to maximise their appeal to an audience or market.
TURF analysis with SPSS Statistics Read More »
In this video Jarlath Quinn explains what cluster analysis is, how it is applied in the real world and how easy it is create your own cluster analysis models in SPSS Statistics.
Cluster Analysis with IBM SPSS Statistics Read More »
Sometimes you may have problems with your data issues not related so much to the values of the data but to the fields themselves, such as awkward field names. The filter node is a really useful tool that offers a bunch of tricks for dealing with awkward fields.
Introduction to the filter node in SPSS Modeler Read More »
In this video we explore variable sets – a procedure in SPSS that allows you to generate subsets of variables or fields for display within dialogue boxes and in the data editor itself.
How to work with variable sets in SPSS Statistics Read More »
Used correctly, the generate menu offers analysts some substantial time saving benefits. Watch this video to learn more about how you can use the generate menu effectively.
Introduction to the generate menu in SPSS Modeler Read More »
SPSS enables quite a high level of customisation so you can set up the software in a way that enables you to be a lot more productive, however many people are unaware of just how powerful these customisation options are. In this video we explore the options edit menu.
How to change the defaults in SPSS Statistics Read More »
The data audit node is a powerful tool you can use to help understand the shape and structure of your data before your analysis begins. You can also make some decisions here regarding how you might want to clean up your data, for example by dealing with missing values or extremes and outliers.
Introduction to the data audit node in SPSS Modeler Read More »
In part one of this video series Jarlath Quinn explains how operational analytics works, what data sources may be utilised and introduces the example case study that forms the basis of the subsequent videos in the series.
Predictive operational analytics part 1 Read More »
In part two of our predictive operational analytics video series, Jarlath Quinn introduces the IBM SPSS Modeler Software before showing how to explore the example data from the case study and carry out text analytics of engineer logs to categorise the information and create key fields for further analysis.
Predictive operational analytics part 2 – SPSS Modeler demo Read More »
In part 3 of this predictive operational analytics guide Jarlath uses the results from the previous analysis stage to show how to build and assess a predictive model that identifies whether or not a part replacement will be required during a maintenance visit.
Predictive operational analytics part 3 – predictive part replacement Read More »
In this final part of our predictive operational analytics video series Jarlath shows how we can use the predictive technology to go further by predicting the actual outcome of the visit including which part is likely to require replacement.
Predictive operational analytics part 4 – predicting task outcomes Read More »
Jarlath provides a brief history of the concept of net promoter score before introducing the case study whereby Predictive Promoter was applied to data from the guests of a major hotel chain.
Predictive promoter part 1 – introducing predictive promoter scoring Read More »
In this video Jarlath shows how to automatically produce a model that predicts customer’s recommendation scores based upon transactional and operational data.
Predictive promoter part 2 – building a net promoter score predictive model Read More »
In this video Jarlath shows how easy it is to take a previously built model that has been generated based on known outcomes and apply it to customer data where the outcome is not known.
Predictive promoter part 3 – scoring with a net promoter score model Read More »
In this final part of our predictive promoter video series, Jarlath Quinn tackles the project’s most ambitious task: mining the open-ended guest comments to uncover important insights. Here you can discover how we can use text analytics to extract a series of concepts and sentiments from customer comments in order to categorise the guests’ responses.
Predictive promoter part 4 – text mining and conclusions Read More »
In this short video Jarlath Quinn demonstrates how to use the powerful simulation tools within IBM SPSS Modeler to perform What If analysis (also known as ‘Scenario Planning’). What if analysis allows business-focused analysts to go beyond simple predictive modelling to evaluate the impact of different choices and scenarios on predicted outcomes.
What If Analysis using IBM SPSS Modeler Premium Read More »
This video shows you how organisations with substantial capital assets can use IBM SPSS Modeler to predict when asset failure is most likely. Predicting asset failure can prevent problems before they happen and enables organisations to save money, reduce asset downtime and increase efficiency.
Predicting asset failure using IBM SPSS Modeler Read More »
