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Logistic Regression
2
day Course This course is suitable for researchers and/or data analysts that are interested in gaining an understanding of categorical data analysis, in particular understanding the theory and and techniques involved in logistic regression and linear regression.
Attendees are not required to have any familiarity with statistical software, however, a basic knowledge of SPSS would be an advantage. Attendees are required to have a basic knowledge of statistics. This course focuses on the theory and analysis of categorica reponse data. In particular, the focus will be on the analysis of binary (Y/N, T/F etc) data and modelling By the end of the course the attendees will have learned the: Analysis of contingency tables (1-way, 2-way and multiway) Analysis of relations and association between categorical variables. Requirements, assumptions and limitations of logistic regression When and why to use logistic regression. Objectives:
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Training Using CRISP DM How to Implement a Data Mining Strategy Logistic Regression ANOVA
What Our Clients Say....... "HABACA, through the CRISP methodology, provides a useful framework for engaging with data mining projects. The process, consistent with best project management practice, provides clarity and consistency in managing projects. It's flexibilty and ease-of-use makes it a useful tool in the armoury of the data miner. The Customer Insight team in Bank of Ireland were happy with the training they received from HABACA and have already begun implementing the CRISP methodology in their datamining projects." Lorna Harding Business Manager Centre of Excellence Bank Of Ireland |
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