Towards A Data Mindset

What you'll learn
What is data mindset
Are averages misleading
Should I reward (or penalize) extreme performance
Is a lag indicator a reliable measure
What are end to end measures
Are inferences from a sample reliable
What are outliers
How to forecast future performance easily
Requirements
None.
Description
In a world driven by data, developing a robust data mindset is crucial for anyone looking to make informed decisions and drive improvement. This course is designed to equip participants with the foundational concepts and tools needed to harness the power of data effectively.Key Topics:What Gets Measured Gets Improved: Introduction to the concept of y=f(x) and understanding that every problem or opportunity can be framed as an equation. This sets the stage for a data-driven approach to improvement.Averages Can Be Misleading: Dive into measures of central tendency versus dispersion and explore the importance of understanding the full picture that data presents.Lead vs. Lag Indicators: Learn the difference between indicators that predict future performance and those that reflect past performance, and how to use them effectively.Measure It Right: Explore the concept of end-to-end measures versus silo measures and the importance of accurate measurement to avoid the illusion of success.Sample It Right: Understand the principles of sampling and how to ensure your data is representative and reliable.Correlation and Causation: Uncover the differences between correlation and causation and the pitfalls of confusing the two.Should You Reward Extreme Performance?: Discuss the concept of regression to the mean and its implications for performance evaluation.Outliers: Learn how to identify and interpret outliers in your data and their impact on analysis.Forecasting: Gain insights into basic forecasting techniques and how to predict future trends based on historical data.This course is designed for anyone looking to enhance their ability to think critically about data and apply data-driven principles to their work or personal life. Whether you're a manager, analyst, or just someone interested in the power of data, this course will provide you with the tools and mindset needed to unlock the insights hidden within data.Disclaimer: Please note that this course is focused on developing a data mindset and is not a technical course on data analysis or data science. It is designed to provide practical insights and foundational concepts for thinking critically about data in decision-making processes.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Characteristics of Data Mindset
Section 2: What Gets Measured Gets Improved
Lecture 3 What Gets Measured Gets Improved
Section 3: Is average a reliable measure
Lecture 4 Averages Can Be Misleading
Lecture 5 Case Studies
Lecture 6 Easy Computations in Excel
Section 4: Lead Vs Lag Indicators
Lecture 7 Lead Vs Lag Indicators
Lecture 8 Examples
Section 5: Measure it right and Sample it right!
Lecture 9 Measure it right
Lecture 10 More Examples
Lecture 11 Sample it right
Lecture 12 More Examples
Section 6: Correlation
Lecture 13 Introduction
Lecture 14 Correlation Vs Causation
Lecture 15 Should you reward extreme performance
Section 7: Logical Fallacies
Lecture 16 Logical Fallacies
Section 8: Outliers
Lecture 17 Outliers
Section 9: Look ahead!
Lecture 18 Forecasting
Professionals,Analysts,Students,Anyone who is curious to explore this topic

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