23/1/11
The introduction session of BI-Workshop was very loaded inspite being an introductory session but it was definitely a very good session. The data looked never so good, meaningful and colourful.
We started with First Level Analysis where we were taught how to calculate Frequencies with the given data sheet. Then we covered Cross Tabulation both for 2 variables as well as 3 variables.
The third and the last technique for the day was Cluster Analysis in which two different types of clusters were covered- Divisive and Agglomerative, both these are types of Hierarchical Cluster.
Hierarchy type of cluster is done for Variables provided the number of objects is less than 50. K-Means type of cluster is done for Cases provided the number of objects is more than 50.
24/1/11
The second session was more relaxed. We started Perceptual Mapping a.k.a PerMap.
PerMap is of two types- Overall Similarity and Attribute Based. In Overall Similarity a thorough knowledge is required what goes in people's minds because of which they think two particular objects are similar/dissimilar. One disadvantage is that the hidden attributes might get exposed.
In Attribute-Based PerMap attributes are provided which gives rise to one major disadvantage, it being the chance missing of an important attribute.
We then learned how to make a PerMap in both the types in two as well as three dimensions and also the significance of Objective Function Value which is nothing but an error and how it gets reduced when PerMap display is changed from Two dimention to Three dimension.
25/1/11
The concluding session was on Factor Analysis wherein we learned how to divide a whole lot of given factors can be divided and then using factor
analysis (extraction method) less important factors can be eliminated.
Z-Scores were also covered in the last session of the workshop where one of the major things that we observed was that the graph of the variable (particularly Horse Power) was similar to the Z-Scores for Horse Power.
Thanks,
Garima Singh
The introduction session of BI-Workshop was very loaded inspite being an introductory session but it was definitely a very good session. The data looked never so good, meaningful and colourful.
We started with First Level Analysis where we were taught how to calculate Frequencies with the given data sheet. Then we covered Cross Tabulation both for 2 variables as well as 3 variables.
The third and the last technique for the day was Cluster Analysis in which two different types of clusters were covered- Divisive and Agglomerative, both these are types of Hierarchical Cluster.
Hierarchy type of cluster is done for Variables provided the number of objects is less than 50. K-Means type of cluster is done for Cases provided the number of objects is more than 50.
24/1/11
The second session was more relaxed. We started Perceptual Mapping a.k.a PerMap.
PerMap is of two types- Overall Similarity and Attribute Based. In Overall Similarity a thorough knowledge is required what goes in people's minds because of which they think two particular objects are similar/dissimilar. One disadvantage is that the hidden attributes might get exposed.
In Attribute-Based PerMap attributes are provided which gives rise to one major disadvantage, it being the chance missing of an important attribute.
We then learned how to make a PerMap in both the types in two as well as three dimensions and also the significance of Objective Function Value which is nothing but an error and how it gets reduced when PerMap display is changed from Two dimention to Three dimension.
25/1/11
The concluding session was on Factor Analysis wherein we learned how to divide a whole lot of given factors can be divided and then using factor
analysis (extraction method) less important factors can be eliminated.
Z-Scores were also covered in the last session of the workshop where one of the major things that we observed was that the graph of the variable (particularly Horse Power) was similar to the Z-Scores for Horse Power.
Thanks,
Garima Singh
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