Skip to main content

What Should be Focused When Making a Decision?

What to be focused?

Have you ever thought about this question? We may have given with a numerous number of data. But what should be our focus?


Statistical data has a significant potential to be misused. Its ability to highlight any statement with any authority is especially dangerous. People will go for the evidence and certain numbers of people who use it or support it. Even if it is wrong in fact, they will claim it to be true. But while incorrect decisions based on misleading data and statistics do a great job, data also has the potential to allow deep insights, drive better decisions, and enable predictions to be made.


But why?

During World War II, the Allied nations' experts mapped bullet holes in fighter planes that were hit by Axis's bullets. They found a pattern and proposed a plan to reinforce the area which was severely hit by the bullets (red dots in the picture).

Theoretically, it was a logical deduction because they were the most affected areas in their flights.

But Abraham Wald, a Hungarian Jewish mathematician, came to a different conclusion. He said that the red dots represented only the damage that happened to the planes which did not affect their flight back to the home runway.


According to him the areas where there were no points should be reinforced because these are the positions where the plane would not survive being hit.


“Gentlemen, you need to put more armour-plate where the holes aren’t, because that’s where the holes were on the planes that didn’t return.” — Abraham Wald

This phenomenon is well known as survival deviation.

If you look at the ones that have survived, this happens when you should dwell on the things that haven't.

What are you looking at in this crisis? Where are you taking bullets or where should we act?

This way of dealing things may help you to see the world in the correct way and to deal with a lot of the unresolved problems. We dramatically reduce the risk of being trapped by knowing some of the most common processes where misleading data and statistics are generated. We actively contribute to a better informed world with the correct implementation of data & statistics in a responsible, understandable and ethical way.

Doesn't that sound like an awesome task for the future?

Hope it can help. Share your thoughts too.

Comments

Popular posts from this blog

A 3000 Years Old Love Story

Pharaoh Ramesses the Great and Queen Nefertari Pharaoh Ramesses II the Great ruled ancient Egypt during the 19th dynasty (1292-1190 BCE). His reign was the second-longest in Egyptian history, lasting from 1279 to 1213 BCE. He assumed the throne in 1279 BC as a royal member of the Nineteenth Dynasty and ruled for 67 years. In Greek sources, Ramesses II was also known as Ozymandias, with the first half of the appellation deriving from Ramesses' regnal name, Usermaatre Setepenre, which means 'The Maat of Ra is mighty, Chosen of Ra'.  He is also recognized as the Egyptian Empire's greatest, most renowned, and most dominating pharaoh. His successors and subsequent Egyptians are reported to have referred to him as the Great Ancestor. Ramesses II was a famous explorer, monarch, and warrior who conducted multiple military excursions to the Levant to reestablish Egyptian dominance over Canaan. He is also supposed to have conducted journeys south to Nubia, which are documented in

Parallel A* Search on GPU

A* search is a fundamental topic in Artificial Intelligence. In this article, let’s see how we can implement this marvelous algorithm in parallel on Graphics Processing Unit (GPU). Traditional A* Search Classical A* search implementations typically use two lists, the open list, and the closed list, to store the states during expansion. The closed list stores all of the visited states and is used to prevent the same state from being expanded multiple times. To detect duplicated nodes, this list is frequently implemented by a linked hash table. The open list normally contains states whose successors have not yet been thoroughly investigated. The open list’s data structure is a priority queue, which is typically implemented by a binary heap. The open list of states is sorted using the heuristic function  f(x) : f(x) = g(x) + h(x). The distance or cost from the starting node to the current state  x  is defined by the function  g(x) , and the estimated distance or cost from the current stat

Sorting Algorithms  : A Comprehensive Guide

Sorting Algorithms  : Explained With Illustrations Sorting is the process of structuring data in a specific format. The sorting algorithm explicitly states how to arrange data in a specific order. The most popular orders are numerical or lexicographical. When humans understood the importance of searching speedily, they coined the term sorting. The significance of sorting stems from the fact that if data is stored in a sorted manner, data searching can be optimized to a very high level. Sorting is also used to make data more readable. The following are a few examples of sorting in real-world scenarios. 1. Telephone Directory: The telephone directory stores people’s phone numbers alphabetically so that the names can be easily searched. 2. Dictionary: Words are stored in alphabetical order in the dictionary, making it easy to find any word. Sorting algorithms can be classified into two types. Integer sorts Comparison sorts Integer sorts Counting sorts are another name for integer sorts (t