AIDA 181: Assignment 4 questions with
100% complete solutions graded A+
Traditional Data Analysis Techniques - correct answer ✔✔1.) Exploratory Data Analysis
2.) Classification Trees
3.) Regression Analysis
4.) Cluster Analysis
these techniques are usually applied to structured data (recall: data organized into databases
with defined fields, including links between databases)
Classification Trees - correct answer ✔✔A supervised learning technique that uses a structure
similar to a tree to segment data according to known attributes to determine the value of a
categorical target variable
Contains nodes, arrows, and leaf nodes
Aka decision tree
Regression Analysis - correct answer ✔✔A statistical technique that is used to estimate
relationships between variables
Cluster Analysis - correct answer ✔✔A model that determines previously unknown groupings of
data
-a technique for unsupervised learning
-typically used when an insurer knows a general problem it wants to solve but doesn't know the
variables it must analyze to do so
, 2 types of descriptions:
-a characteristic description describes the typical attributes of the cluster
-a differential description describes the differences between the instances of one cluster and
those of other clusters
Also uses k nearest neighbor (k-NN)
Exploratory Data Analysis - correct answer ✔✔Through this, an analyst can develop a basic
understanding of the data and obtain information about missing/inaccurate data
-involves charts/graphs that show data patterns and correlations among data
Scatter plots, bubble plots, correlation matrix
Leaf Node - correct answer ✔✔Indicates the values of the target variable (recall: the predefined
attribute whose value is being predicted in a data analytical model)
In a Classification Tree, a node that is used to classify an instance based on its attributes
Linear Regression - correct answer ✔✔A statistical method to predict the numerical value of a
target variable based on the values of explanatory variables
-predicts a numerical value for the target variable as a function of one or more attributes
(explanatory variables)
-assumes the predicted value changes proportionally with the attribute values
Can be shown as a straight line on a 2D graph
-x axis is the value of the attribute (explanatory variable)
-y axis is the target variable
100% complete solutions graded A+
Traditional Data Analysis Techniques - correct answer ✔✔1.) Exploratory Data Analysis
2.) Classification Trees
3.) Regression Analysis
4.) Cluster Analysis
these techniques are usually applied to structured data (recall: data organized into databases
with defined fields, including links between databases)
Classification Trees - correct answer ✔✔A supervised learning technique that uses a structure
similar to a tree to segment data according to known attributes to determine the value of a
categorical target variable
Contains nodes, arrows, and leaf nodes
Aka decision tree
Regression Analysis - correct answer ✔✔A statistical technique that is used to estimate
relationships between variables
Cluster Analysis - correct answer ✔✔A model that determines previously unknown groupings of
data
-a technique for unsupervised learning
-typically used when an insurer knows a general problem it wants to solve but doesn't know the
variables it must analyze to do so
, 2 types of descriptions:
-a characteristic description describes the typical attributes of the cluster
-a differential description describes the differences between the instances of one cluster and
those of other clusters
Also uses k nearest neighbor (k-NN)
Exploratory Data Analysis - correct answer ✔✔Through this, an analyst can develop a basic
understanding of the data and obtain information about missing/inaccurate data
-involves charts/graphs that show data patterns and correlations among data
Scatter plots, bubble plots, correlation matrix
Leaf Node - correct answer ✔✔Indicates the values of the target variable (recall: the predefined
attribute whose value is being predicted in a data analytical model)
In a Classification Tree, a node that is used to classify an instance based on its attributes
Linear Regression - correct answer ✔✔A statistical method to predict the numerical value of a
target variable based on the values of explanatory variables
-predicts a numerical value for the target variable as a function of one or more attributes
(explanatory variables)
-assumes the predicted value changes proportionally with the attribute values
Can be shown as a straight line on a 2D graph
-x axis is the value of the attribute (explanatory variable)
-y axis is the target variable
