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Advanced Analytical Theory And Methods.edited

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Running head: ADVANCED ANALYTICAL THEORY AND METHODS 1
Advanced Analytical Theory and Methods
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ADVANCED ANALYTICAL THEORY AND METHODS 2
Advanced Analytical Theory and Methods
Answers to questions
a. In the use of a categorical variable with n possible values, explain the following:
1. Why only n 1 binary variables are necessary
The reason as to why on n-1 binary variables are necessary is because if we consider
the vast majority, dummy variables are always statistical and can accurately encode
information represented by the categorical variables. More so, the number of dummy
variables needed in describing a given categorical variable depends on the number of
values the categorical variable can assume. That is why the n-1 binary variable is
necessary to represent a categorical variable of n values.
2. Why using n variables would be problematic
Using the n variable will be problematic. This is because algorithms are dependent on
covariance calculations such as regression and also requires numerical operations
which mean that they must operate on numbers. More so, note that dummy variables
are used to transform categorical data to numeric therefore when they are excluded in
an analysis; a poor fit of the model will be created.
b. Describe how logistic regression can be used as a classifier.
Logistic regression is a measure of the relationship between dependent variables in the
categorical variable and one or more independent variables through probability
estimation of a logistic function (Cattelan & Varin, 2018). This means that a logistic
regression classifier is more of a linear classifier. It utilizes calculated scores in predicting
the target class. The calculated logits for every model of linear regression are passed
through the softmax function which produces probabilities for each of the provided

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Running head: ADVANCED ANALYTICAL THEORY AND METHODS Advanced Analytical Theory and Methods Name of student Institutional affiliation Course Date 1 ADVANCED ANALYTICAL THEORY AND METHODS 2 Advanced Analytical Theory and Methods Answers to questions a. In the use of a categorical variable with n possible values, explain the following: 1. Why only n – 1 binary variables are necessary The reason as to why on n-1 binary variables are necessary is because if we consider the vast majority, dummy variables are always statistical and can accurately encode information represented by the categorical variables. More so, the number of dummy variables needed in describing a given categorical variable depends on the number of values the categorical variable can assume. That is why the n-1 binary variable is necessary to represent a categorical variable of n values. 2. Why using n variables would be problematic Using the n variable will be problematic. This is because algorithms are dependent on covariance calculations such as regression and also requires numerical operations which mean that they must operate on numbers. More so, note that dummy variables are used to transform categorical data to numeric therefore when they are excluded in an analysis; a poor fit of the model will be created. b. Describe how logistic regression can be used as a classifier. Logistic regression is a measure of the relationship between dependent variables in the categorical variable and one or more ind ...
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