COMPUTATIONAL STATISTICS (CB304)-Computer Science and Business System (CSBS) (III) | RGPV

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• Syllabus

• Syllabus - COMPUTATIONAL STATISTICS (CB304)

• Multivariate Normal Distribution

• Multivariate Normal Distribution Functions
• Conditional Distribution
• Estimation of parameters

• Discriminant Analysis

• Statistical background
• Linear discriminant function analysis
• Estimating linear discriminant functions

• Principal Component Analysis

• Principal components
• Algorithm for conducting principal component analysis
• Deciding on how many principal components to retain
• H-plot

• Factor Analysis

• Factor analysis model
• Extracting common factors
• Determining number of factors
• Transformation of factor analysis solutions
• Factor scores

• Clustering

• Introduction to Clustering
• Types of clustering
• Correlations and distances
• Clustering by partitioning methods
• Hierarchical clustering
• Overlapping clustering
• K-Means Clustering

• Python Concepts, Data Structures, Classes

• Interpreter, Program Execution
• Statements, Expressions, Flow Controls
• Functions, Numeric Types, Sequences
• Class Definition, Constructors
• Text & Binary Files

• Data Wrangling

• Combining and Merging Datasets
• Reshaping and Pivoting
• Data Transformation
• String Manipulation, Regular Expressions

• Data Aggregation, Group Operations, Time series

• GoupBy Mechanics
• Data Aggregation
• Groupwise Operations and Transformations
• Pivot Tables and Cross Tabulations
• Time Series Basics

• Visualization in Python

• Matplotlib package
• Plotting Graphs
• Controlling Graph
• Adding Text
• More Graph Types
• Getting and setting values
• Patches