There is a saying, “No matter how busy you are, you can't use a needle at your back.”
In dictionary terms, this phrase means that work cannot be done properly by breaking the necessary order or ignoring formality.

What should I learn first in order to be good at data analysis?

Nowadays, there is a lot of enthusiasm for learning data analysis techniques in Python, R, and coding.

However, after learning such a programming language, they gave up halfway because coding was difficult,

Even after completing a coding course, I easily encounter people around me who are uncertain about how to interpret or use data analysis results.

I've seen many such students while teaching data analysis courses at university.

What such people have in common is that they are only learning skills without properly understanding the statistical knowledge that is the foundation of data analysis.

Dealing with data in statistical thinking is a shortcut!

“Coding is hard to follow, even statistics?” You might be asking the question.

However, I can't use a needle at the waist!

Coding isn't fun if you can't understand what the results of data analysis mean.

When I see students struggling to use Python or R as data analysis tools at school, I would rather recommend studying using GUI (graphical user interface) -based tools such as Excel or Jamovi (Jamovi).

Years of experience in education have proven that my principles for learning data analysis are the right path.

Why do we need to analyze data? What kind of data do you need? Data analysis can only be fun if you go through this whole series of processes from beginning to end, how to collect data, how to analyze it, and how to interpret it.

Who are you making this course for?

This course is based on the concept of statistics, which is the foundation and core idea of data analysis.

It is designed so that anyone can have a practical data analysis experience using Excel and Jamovi (Jamovi), which can be easily used.

In particular, for jobs such as customer management, human resources management, and quality control that require data analysis capabilities in business

We used practical data as examples that current employees can relate to and easily understand.

Are you a supporter? Don't worry.

With the exception of hard and uninteresting mathematical problems, it deals only with statistical principles with a focus on conceptual understanding.

If you follow the content of the lesson step by step,

You'll find yourself full of confidence in data analysis.

Actual data analysis using Jamovi (Jamovi) and Excel

Actual data analysis using Jamovi (Jamovi) and Excel