Data Analytics Final Exam with
Accurate Solutions
Three advanced data analytics techniques - ANSWER-decision trees
clustering
association rules
Decision trees - ANSWER-Type of classification method to determine membership of
cases or values of an outcome variable based on one or more predictor variables
What predicts whether a company will go bankrupt?
(using different variables to predict)
How likely is it going to rain tomorrow?
Outcome variable is categorical
In a real situation, the decision tree software has to deal with instances where -
ANSWER-The same set of predictors resulting in different outcomes
Multiple paths result in the same outcome
Not every combination of predictors is in the training set
Clustering - ANSWER-Used to determine distinct groups of data
Based on data across multiple dimensions
Uses:
-customer segmentation
-identifying patient care groups
-performance of business sectors
1. define variables
2. install and load packages
3. read csv data
4. preprocressing data
-remove missing data
-normalizing
-remove outliers
5. cluster analysis
-comparing different solutions with number of clusters
-running cluster analysis with given number of clusters
-interpreting the results
, Psych package - ANSWER-Used for descriptive statistics
Variable Assignment - ANSWER-names containers for data
= or ->
can start with letters or digits
case sensitive
rmv() removes the variable from memory
x,y, z are variables that can be manipulated
Functions - ANSWER-Performs an action, like installing a package or loading a library.
You know its a functions because there are parenthesis after the command.
Accept parameters (in parenthesis) and return a value
sqrt()
log()
abs()
exp()
c()
rep()
length()
min()
max()
mean()
median()
sd()
var()
summary()
kmeans()
require()
install.packages()
scale()
Variables - ANSWER-Named containers for data
Numeric Data Types - ANSWER-Numbers
-1
-2.5
Character Data Type - ANSWER-Text strings:
"Mark"
"red"
Boolean data Type - ANSWER-Logical:
TRUE or FALSE
female <- TRUE
Accurate Solutions
Three advanced data analytics techniques - ANSWER-decision trees
clustering
association rules
Decision trees - ANSWER-Type of classification method to determine membership of
cases or values of an outcome variable based on one or more predictor variables
What predicts whether a company will go bankrupt?
(using different variables to predict)
How likely is it going to rain tomorrow?
Outcome variable is categorical
In a real situation, the decision tree software has to deal with instances where -
ANSWER-The same set of predictors resulting in different outcomes
Multiple paths result in the same outcome
Not every combination of predictors is in the training set
Clustering - ANSWER-Used to determine distinct groups of data
Based on data across multiple dimensions
Uses:
-customer segmentation
-identifying patient care groups
-performance of business sectors
1. define variables
2. install and load packages
3. read csv data
4. preprocressing data
-remove missing data
-normalizing
-remove outliers
5. cluster analysis
-comparing different solutions with number of clusters
-running cluster analysis with given number of clusters
-interpreting the results
, Psych package - ANSWER-Used for descriptive statistics
Variable Assignment - ANSWER-names containers for data
= or ->
can start with letters or digits
case sensitive
rmv() removes the variable from memory
x,y, z are variables that can be manipulated
Functions - ANSWER-Performs an action, like installing a package or loading a library.
You know its a functions because there are parenthesis after the command.
Accept parameters (in parenthesis) and return a value
sqrt()
log()
abs()
exp()
c()
rep()
length()
min()
max()
mean()
median()
sd()
var()
summary()
kmeans()
require()
install.packages()
scale()
Variables - ANSWER-Named containers for data
Numeric Data Types - ANSWER-Numbers
-1
-2.5
Character Data Type - ANSWER-Text strings:
"Mark"
"red"
Boolean data Type - ANSWER-Logical:
TRUE or FALSE
female <- TRUE
