Regression trees are a very interesting data analysis technique commonly used in tasks related to poststratification, forecasting, and segmentation. It is also a very useful technique for data exploration, identifying the structure of relationships among variables, and finding the best predictors. A set of clear rules are visualised in tree form which split the dataset into smaller segments with different mean values of the predicted variable. This makes regression trees great for estimating customer value, forecasting consumer shopping value, or predicting the duration of website visits. They can be an extension of linear regression or variance analysis techniques. WIĘCEJ
Positioning a product in the context of the competition, or the identification of a product’s features and attributes are often key issues facing marketing, promotion, and product managers . Emphasizing a product’s key advantages and features helps adapt the promotional message to the expectations of potential customers, and knowing the strengths of your competition makes it is easier to plan an effective promotional strategy. WIĘCEJ
In our previous articles about the Automatic linear modeling procedure of IBM SPSS Statistics / PS IMAGO PRO, we discussed the result viewer and methods for selecting variables for the model. Today, we will look into ensemble model methods. WIĘCEJ
The Automatic linear modeling procedure is intended to streamline the work of analysts who use regression models. LINEAR (in the IBM SPSS Statistics command language) is the little sister of REGRESSION. One of the key differences between them is the variable selection method, which will be the focus here. Other differences are discussed in the WIĘCEJ
Both business and science undertake research to survive and thrive. It is invariably a complex process that requires not only knowledge but also experience. Ultimately, however, data is always key, which will be my focus here. This post will attempt to define data, its purpose, whether or not it can be classified using specific criteria, and whether data comes solely from research. WIĘCEJ
How can we estimate the potential value of consumer shopping, predict the behavior of a visitor to our website, or reduce the risk of credit losses? Analysts have a rich set of statistical techniques at their disposal that allow them to find distinct patterns in a customer’s behavior that are important from a business point WIĘCEJ
In this article I will introduce Automatic linear modelling, a procedure for linear models available in PS IMAGO PRO.
This procedure is intended to make life easier for those who work on large datasets and want to use regression models. Automatic linear models lack many advanced settings and options for model exploration that can be found in other regression procedures. On the other hand, as with other procedures of this kind, it speeds up and streamlines data processing. WIĘCEJ
The decision tree is a popular and effective algorithm used primarily in classification work, but it also serves well in predicting quantitative phenomena. The charm of methods based on decision trees comes mainly from the fact that they present us with a set of convenient decision, or business rules. WIĘCEJ
Today, we will look into Social Network Analysis (SNA), or Social Relation Analysis. SNA is the investigation of a community through the study of relationships between its members. It combines statistics, sociology, and social psychology. It is not, however, merely a theoretical concept, but more rather another source of knowledge that is gaining in popularity WIĘCEJ
The dashboard is a form of reporting, which allows the analyst to convey information in a concise way. The dashboard report is usually a one-pager showing the current and historical information on key indicators. Such reports are usually prepared for managers to help them make quick decisions. WIĘCEJ
This blog is devoted to data collection and analysis with articles that aim to inspire data analysts from across the business world, academia and public sector. Our articles endeavor to inform, educate and entertain with one goal in mind: to show how to transform data into clear, attractive and usable information. We invite you to read and share.