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
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
When measuring a phenomenon, you need to select the right tool. To measure temperature, you use a thermometer; alcohol content in breath is measured with an alcometer; and weight, with bathroom scales. In survey research, the measuring tool is the questionnaire and its questions. WIĘCEJ
When creating a table, you can present weighted or unweighted data. As usual, the answer depends on the situation. You will get my meaning in a minute, but first, let me explain briefly what weighting adjustment is. In representative studies, you want to generalise sample results for the whole population. In order to achieve this, WIĘCEJ