Tarastats Statistical Consultancy

Decision making 7.0 - Statistical thinking for Leaders

Decision making 7.0 for Leaders

1 250,00 €

Short Courses

Understanding statistics – the science that turns data into information – is becoming the required principal competency for decision makers of all types. Its core ingredient – statistical thinking – is becoming as valuable as the skills of reading and writing.

Decision making 7.0 courses equip you with tools and techniques to develop statistical thinking and enhance your decision-making in the world of data and mass information.

Read more about Decision making 7.0 here.

If you are interested in online learning, check out our ONLINE COURSES.

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About courses

What are the key outcomes of the courses?

  • THINK OBJECTIVELY: to become familiar with the thinking methodology behind statistical thinking
  • UNDERSTAND OBJECTIVELY: to develop a profound understanding of the key statistical concepts
  • SEE OBJECTIVELY: to become familiar with causal thinking concepts

What will you do during the course?

  • EXPLORE the importance of objective information when solving problems and developing strategies
  • EQUIP yourself with tools, techniques and data thinking; to support you when in search of accurate and objective information
  • IMPROVE your understanding about the reliability of data insights provided by data analysts, scientists and media reporting
  • EXPAND your understanding about why ‘correlation is not causation’; and how causal thinking impacts analysis results and obtained insights.

More information about the covered topics is provided in the above tabs: ‘Course 1’ and ‘Course 2’.

About the learning methodology

The courses are organised in an interactive way and comprise a mixture of presentations, discussions, and individual work. A deep-learning and experiential teaching approaches are used. Participants’ thinking is challenged by a number of real world examples. The interaction among participants and instructor is important, thus, each course is limited to 15 participants.

About the instructor

Dr. Ana Kolar has significant experience in teaching at university level. She is able to introduce and explain complex topics in a simple manner and she strives towards an educational approach that is based on experiential learning. Ana is the creator of the new approach for developing statistical thinking skills – the essential skills for effective decision-making in the digital era. Read more about Ana here.

About Statistical Thinking

What is Statistical Thinking?

Statistical thinking is a thought process that enables a subject or a situation to be analysed objectively. It provides our minds with a thinking methodology that is founded on the key statistical concepts and which empowers the process of turning data and information in to reliable insights. In view of that, statistical thinking effectively supports problem-solving practices, strategy developments and solution-seeking procedures.

A ‘human mind data analysis’ versus a ‘statistical data analysis’

Human minds work according to the evidence-based principle – information and data our minds are exposed to are the foundation for our minds’ decision-making process. Our minds collect information, analyse it and form conclusions. A statistical data analysis does it similarly, but with one important difference: the process of collecting data, analysing and forming conclusions is done according to the methodology that assures objectivity and supports the notion of finding the truth. Statistical thinking is the crucial part of this methodology.

How do we help you to develop Statistical Thinking skills?

We introduce you the processes and the thinking that is used in statistical data analysis. We provide you with an experience that enables you to develop not only statistical thinking, but also a profound understanding of the key data analytics concepts.

Course I

The course emphasizes the development of statistical thinking skills to support objective decision-making, effective problem-solving and strategy developments. No prior knowledge of basic statistical concepts is required.

Covered topics

ON THE ROAD TO OBJECTIVITY

In the first part of the course we get familiar with the “thinking mechanism” behind statistical thinking. We explore the key statistical and non-statistical concepts required for developing statistical thinking skills. We look at what causal thinking is and how it influences our understanding of data and information we are exposed to.

UNDERSTANDING ORIGINS OF BIASES

In the second part of the course we talk about different types of biases and the importance of understanding their origins. We explore the ways to recognise, remedy or avoid biases. We look at how biases impact accuracy of data, information and decision-making.

MANAGING UNCERTAINTY

In the last part of the course we discuss objective critical thinking and provide tools to judge data insights obtained from data analysts, data scientists and media reporting. We show:

  • why AI algorithms are biased and unfair and how to avoid pitfalls on your AI journeys,
  • how to deal with uncertainty when predicting,
  • what questions to ask to validate accuracy of data insights.

Additional information

For more information about statistical thinking, learning methodology used in courses, size of classes and presentation of the instructor, please check the tab ‘About courses’ and ‘About Statistical Thinking’.

 

Course II

The course is the continuation of the Course I. Statistical thinking skills are further developed to support objective decision-making, effective problem-solving and strategy developments.

Covered topics

EXPLORING OBJECTIVITY WHEN IN SEARCH OF ACCURATE INFORMATION

We continue from the previous course to develop statistical thinking skills. We explore different numerical and qualitative tools to help us in judging accuracy of information. We learn to acknowledge variation in order to understand uncertainty.

EXPLORING POWER(LESSNESS) OF EXPERIMENTS IN PRODUCING ACCURATE INFORMATION

We look at the importance of understanding design – how experiment is designed. Understanding the design means understanding accuracy of information that is derived from experiment. Correlation versus causation.

THE ROLE OF CAUSAL THINKING WHEN JUDGING ACCURACY OF INFORMATION

We look at how to spot fallacy in data insights, how to understand biases of social media data insights, why bias-proof algorithms don’t exist and how to account for that. We also show why it is not statistics that lies, but people who use it and report about it.

Additional information

For more information about statistical thinking, learning methodology used in courses, size of classes and presentation of the instructor, please check the tab ‘About courses’ and ‘About Statistical Thinking’.

 

Upcoming courses

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