Causal Analysis Training
Causal analysis training equips professionals with the skills and tools necessary to determine the underlying causes of specific problems or phenomena. By understanding causal relationships, participants can improve decision-making, optimize processes, and prevent issues from recurring. The course usually blends theoretical concepts with practical applications, teaching various methods to uncover and verify causal factors.

Why should you choose Nisa For Casual Training?
Nisa Trainings is the best online training platform for conducting one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and happy to clarify your doubts anytime. Our teaching style at Nisa Trainings is entirely hands-on. You’ll have access to our desktop screen and will be actively conducting hands-on labs on your desktop.
Job Assistance
If you face any problem while working on Casual Course, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.
The Process we follow for our Online Job Support Service:
- We receive your inquiry for Online Job
- We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re
- If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, we will only agree to provide service. And then you have to make the payment to get the service from
- We will fix the timing for Online Job Support as mutually agreed by you and our consultant.
Course Information
Casual Training
Duration: 25 Hours
Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)
Training Method: Instructor Led Online One-on-One Live Interactive
Sessions.
COURSE CONTENT :
1. Introduction to Causal Analysis
- Definition and Importance of Causal Analysis
Understand what causal analysis is and why it’s crucial in problem-solving. - Applications and Use Cases
Real-world applications in different industries (e.g., manufacturing, healthcare, business).
2. Causal Thinking
- Basic Causal Inference Concepts
Explanation of correlation vs. causation. - Causal Diagrams
Use of tools like Fishbone diagrams, Causal Loop diagrams, and Flowcharts.
3. Causal Analysis Methodologies
- Root Cause Analysis (RCA)
Techniques like the 5 Whys, Fault Tree Analysis (FTA), and Failure Mode and Effect Analysis (FMEA). - Statistical Methods for Causal Analysis
Regression analysis, path analysis, and propensity score matching.
4. Tools for Causal Analysis
- Data Collection Techniques
How to collect data for causal studies, including experimental and observational data. - Statistical Tools
Overview of software or statistical tools commonly used for causal inference (e.g., R, Python, SPSS).
5. Verifying Causal Relationships
- Criteria for Establishing Causality
Methods to confirm a true causal relationship (e.g., Bradford Hill Criteria). - Bias and Confounding Factors
Identifying and mitigating confounders that can distort causal conclusions.