Statistical models Assignment

This week you will look at a statistics case study and analyze the different types of statistic analysis. Please summarize what you learned in 1/2 page. CREDIT GUARANTEE CORPORATION: ACCOMMODATING AN EXPANSION STRATEGY—NOTE Tuhin Sengupta and Shrestha Pratik wrote this technical note as an aid to instructors in the classroom use of the case Credit Guarantee Corporation: Accommodating an Expansion Strategy, No. 9B17M177. This technical note should not be used in any way that would prejudice the future use of the case. This publication may not be transmitted, photocopied, digitized, or otherwise reproduced in any form or by any means without the permission of the copyright holder. 

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Statistical models
Student’s Name
Institution Affiliation

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Statistical Models
Statistical models
This is the process of making predictions using historical data. There are two variables that has
to be present and these are independent and dependent variables. For instance, if one wants to
predict the revenue for Company A, he/she should obtain historical data for the variables that
affected revenue in the past. In that case, revenue becomes the dependent variable and other
variables such variable costs such as fixed costs and production efficiency becomes the
independent variables.
Score card models
This model makes prediction about the future by measuring characteristics in the model
quantitatively. Each characteristic is divided into different ranges and different scores are
assigned to each of the ranges. In order to assign accurate scores, statistical measures such as K-
means, clustering, data analysis using statistical software such as R and SAS are used. In the end,
the final score card model will contain all the information that regarding different ranges and
their corresponding partial scores.
Decision trees
This is a graphical representation of the results obtained after analyzing predictive models. Each
of the characteristic in the data acts like a node that attaches to the branch of a tree. The results of
the analysis are attached at as a leaf in the branch of the tree.
Random Forest
This model represents trees of egression models that have not been processed to determine the
correct values that should be assigned to them. A boot strap approach is used to sample the data

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randomly that is being used in the model. Once a the number of trees selected are large enough,
the most popular tree is voted for to be the best representative of the model.
Standard Model (Basel 2 frame work)
This model uses a standard format where variables are assigned values to be used in the actual
model
NN network
This model simply uses data architecture to come up with the most appropriate model for a given
set of data.
Rete Algorithim
This method requires one to match different algorithms. These are the used to anlayze the
performance of the systems