Statistical Data Analysis

Track: Enterprise Data Analyst (EDA)

With the overwhelming volume of data available to organizations and businesses, it is important to correctly interpret its implications and have the ability to sort through all this information.

Duration: 3 days
Fee: Request
Start Date: Request

Communicate Statistical Results Effectively

This course will equip participants with the knowledge to develop data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, data wrangle and data visualization.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;

Comprehend the principles, techniques, and practices relevant to Statistics
Conduct Hypothesis Testing

Who should attend:

Professionals that work with data

3 days of in depth learning

Face to face with experienced Data Scientist.

Course Methodology

This course will utilize a combination of Presentations and Workshops.

Pre-requisite:
Python Programming II or R Programming II

HRDF Claimable

HDRF claimable. EPP option available for selected credit card.

CADS Certification

Earn certification upon completion.

Minimum Qualification:
Undergraduate Degree

Training Track

Enterprise Data Analyst (EDA)

Statistical Data Analysis is one of the modules under our Enterprise Data Analyst (EDA) program. EDA is a 28-day training program that provides analysts with the tools to be immediate contributors to a data science team. They will assist to frame business requirements as analytics models.

Details of Subject

Day 1

Introduction to Probability and statistics –
- Expectation, variance, quantiles
- Sampling
- Simulation
- Distribution
- Probability distribution function

Day 2

Main distributions (incl. what are they used for) –
- Discrete/continuous distributions
- Binomial, geometric and Poisson distribution
- Exponential and normal distribution
- Central limit theorem

Day 3

Hypothesis/statistical testing –
- Test of hypothesis on one and two population parameters
- Chi-square test of independence
- Type I and type II error

Lead Instructor

Dr. Vinod A. R. Ramachandran

Dr. Vinod Ramachandran is a certified Data Science specialist with 10 years of Data Modelling experience. His expertise also covers Statistics and Computational Intelligence where he researched the implementation of computational algorithms and techniques in the medical field (A full list of his publications is available at www.goo.gl/S2CC2i). On top of that, Dr. Vinod has also been granted a patent for his work on applying Genetic Algorithms in modelling Epileptic Seizures. Currently, his interests revolve around not only Data Science but also Geometric Modelling and Topological Data analysis.

CADS Certification

EDA CADS Certified Enterprise Data Analyst

Certification information for this module & track will be made available soon.

Hear from Our Alumni

The training has benefited me a lot with the skills required to be a data analyst and has upskilled me in data analysis. What I like about the program is where real life problems in the office is used as the materials during the trainings which provides more understanding of the topics. Eventually, it has broaden up my market in the career development.

The program started by setting an expectation on Day 1, that it is not a Read-And-Pass syllabus. The beauty of this program is that it requires the trainees to get their hands dirty and do the actual work throughout the course. It is indeed very different from a lot of programs in the market which just produces a certificate in the end without the trainee actually able to do some real stuff. The course is definitely benefiting anyone who really want to do Machine Learning and Data Science, by creating talents who are able to connect human thought with the machine algorithm, being the bridge within the corporate, into the digital worlds.

The training was beneficial as it trains myself to think from another perspective - one that may not be new, but wasn't practiced as often as I'd like. It was fun and interactive thanks to the facilitator, Jay, too. He was very helpful to answer any questions the attendees have. Believe that this training gives the attendees an extra edge by giving them the knowledge and perspective on how to better utilize data to what they want/need to do - for the organization, the business, and even for personal use, of which I believe will bring myself further in my career.

The training has been an eye opener for me. As someone who is not of programming background, it introduces me to the possibilities of what data can do. It has also helped me bridge the difference in thinking between the Business Team and the Data Science Team. Had a great time learning!

This training enhance on my skill of analyzing of using another tools of programming instead of excel and how to model and visualized our data in a better way instead of our traditional way. Especially when involve with a large scale of data. If using excel, there will a lot of time consuming there instead of R. For me, in market nowadays of big data, this course will brings more value and create another point of view on how to visualize our data especially in making any decision. And of course will enhance our career development.

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Statistical Data Analysis

Statistical Data Analysis

Communicate Statistical Results Effectively

Learning outcome: