Fundamentals of Statistics
Business Analytics for Decision Making
Welcome
Syllabus
Introduction to Business Analytics
1
An overview of Business Analytics
2
Types of Business Analytics
R Basics
3
Overview of R and RStudio
4
R Syntax and R Script
5
R Markdown
6
Data types, Operators, Statements, and Structures in R
7
Functions and Looping in R
8
Packages and Libraries in R
9
Directories and projects in Rstudio
10
Data Handling in R
Python Basics
11
Understanding Python
12
Jupyter Notebook
13
Data types in Python
14
Operators in Python
15
Numpy
16
Pandas
17
Scipy
Fundamentals of Statistics
18
Introduction to Statistics
19
Descriptive Analytics
20
Fundamentals of Statistical Tests
21
Diagnostic Analytics
22
Choose the Right Test for Data Analysis
Parametric Tests
23
Introduction to Parametric Tests
24
Z-test
25
T-test
26
ANOVA
27
Correlation
Non- Parametric Tests
28
Introduction to Non- Parametric Tests
Tests for Nominal data
29
Introduction to Nominal Tests
30
Chi Square Test
31
McNemar test
32
Cochrans Q Test
33
Phi Coefficient of Correlation
34
Binomial Test
Tests for Ordinal data
35
Introduction to Ordinal Tests
36
Mann-Whitney U Test
37
Kruskal-Wallis Test
38
Friedman Test
39
Wilcoxon Signed-Rank Test
40
Spearman Rank Correlation Scale Tests
Data visualization
41
Introduction to Data visualization
42
Scatter plot and Histogram
43
Bar Charts - One Dimensional
44
Pie Chart - Two Dimensional
45
Line Plot Using R Graphics and R Commander/R Deducer
46
Box plot
Fundamentals of Statistics
Introduction to Statistics
Descriptive Analytics
Fundamentals of Statistical Tests
Diagnostic Analytics
Choose the Right Test for Data Analysis
17
Scipy
18
Introduction to Statistics