Best Statistical Testing Courses Online & Certification

Overview

Curriculum

Mentor

Reviews

Ever wondered how data can tell a story? Our Statistical Testing course takes you on a journey to uncover insights hidden in numbers. Learn to compare multiple groups with ANOVA and explore alternatives for data that doesn’t follow standard patterns. Discover how to measure paired differences with the paired t-test and the Wilcoxon Signed-Rank Test, all explained with real-life examples and hands-on exercises. By the end, you’ll confidently analyze data, interpret results, and make smarter decisions, whether for research, business, or everyday problem-solving.

1.1

Null and Alternative Hypotheses
Type I and Type II Errors, Significance Level (α), Power of a Test
Assumptions in Parametric vs Non-Parametric Tests
Choosing the Right Test for Paired and Repeated Measures Data

2.1

Concept of Dependent Samples
One-Tailed vs Two-Tailed Paired t-Tests
Applications

3.1

Introduction to Wilcoxon Signed-Rank Test
Assumptions of the Test
Step-by-Step Procedure

4.1

Concept of Between-Group and Within-Group Variability
One-Way ANOVA – Definition and Assumptions
Step-by-Step Procedure
Two-Way ANOVA – Introduction and Applications

5.1

Concept and Need for Post-hoc Analysis
Common Post-hoc Tests (Tukey’s HSD, Bonferroni, Scheffé, Duncan’s Test)
Step-by-Step Calculation of Tukey’s HSD

6.1

Introduction to Friedman Test as a Non-Parametric Alternative to Repeated Measures ANOVA
Assumptions of Friedman Test
Step-by-Step Procedure

7.1

Numerical Example using Paired t-Test

8.1

Numerical Example using Wilcoxon Signed Rank Test

9.1

Numerical Example using ANOVA Test

10.1

Numerical Example using Post-hoc Test

11.1

Numerical Example using Friedman Test

12.1

Python Implementation of Paired t-Test

13.1

Python Implementation of Wilcoxon Signed Rank Test

14.1

Python Implementation of ANOVA Test

15.1

Python Implementation of Post-hoc Test

16.1

Python Implementation of Friedman Test

4.8

5 Ratings

Reviews

Rohan Mehta

( Excellent statistics course. )

"This course clearly explains hypothesis testing and statistical analysis methods. The examples helped me understand how statistical tests are applied in research and data science."

Kavya Sharma

( Very clear and practical. )

"The instructor explains tests such as t-tests, ANOVA, and non-parametric methods with simple numerical examples."

Sanjay Rao

( Great for research students. )

"This course helped me understand how to interpret statistical results and validate experimental findings."

Neha Kapoor

( Well explained concepts. )

"The course provides clear explanations of statistical testing methods with real research scenarios."

Aditya Verma

( Highly informative course. )

"A great learning experience for understanding how statistical tests support data-driven decision making."

Statistical Testing Courses & Certification

₹1000

₹6000

Live Learning Sessions - 2hrs

Join live classes to gain deeper insights and direct feedback from expert instructors.

This course includes:

Validity:

60 days
Validity:

60 days
Category:

Data Analysis
Lessons:

7
Students:

1300
Language:

English
Certificates:

Yes