Syllabus

Introduction to Business Analytics

• Understanding Business Analytics
• Types of Business Analytics

R Basics

• Overview of R and RStudio
• R Syntax and R Script
• R Markdown
• Data types, Operators, Statements, and Structures in R
• Functions and Looping in R
• Packages and Libraries in R
• Directories and projects in Rstudio
• Data Handling in R

Python Basics

• Understanding Python
• Data types in Python
• Operators in Python
• Numpy
• Pandas
• Scipy

Fundamentals of Statistics

• Introduction to Statistics
• Descriptive Analytics
• Fundamentals of Statistical Tests
• Diagnostic Analytics
• Choose the Right Test for Data Analysis

Parametric Tests

• Introduction to Parametric Tests
• Z-test
• T-test
• ANOVA
• Correlation

Non- Parametric Tests

• Introduction to Non- Parametric Tests

• Tests for Nominal data

  • Introduction to Nominal Tests
  • Chi Square Test
  • McNemar test
  • Cochrans Q Test
  • Phi Coefficient of Correlation
  • Binomial Test

• Tests for Ordinal data

  • Introduction to Ordinal Tests
  • Mann-Whitney U Test
  • Kruskal-Wallis Test
  • Friedman Test
  • Wilcoxon Signed-Rank Test
  • Spearman Rank Correlation Scale Tests

Data visualization

• Introduction to Data visualization
• Scatter plot and Histogram
• Bar Charts
• Pie Chart
• Line Plot Using R Graphics and R Commander/R Deducer

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