ECONOMICS

Detailed explanation-1: -Being skeptical of others’ work is a good place to start, but a great data scientist should be the most critical and skeptical of their own hypotheses, models, and findings.

Detailed explanation-2: -A truly great data scientist is able to solve valuable business problems in a way that will generate maximum, and in many cases, enduring value. To do this a data scientist needs to understand and make the rights trade-offs between complexity and simplicity.

Detailed explanation-3: -Whatever the task in hand, the most important thing is to be skeptical. We need to question the assumptions around the data and analysis methods. The more we question, the more we know about the truth. Then, we will be able to decide which analysis methods that fit best to our data.

Detailed explanation-4: -The average Data Scientist is most likely skeptical, reserved, and analytical. They tend to be serious and exacting in their work, often seeking to establish procedures that can help others improve, as well. Don’t be surprised if they communicate with excessive detail.

Detailed explanation-5: -Patil’s definition of a data scientist is that it limits data science to activities involving machine learning. According to the reading, how does the author define data science? Data science is some data and more science. Data science is a way of understanding things and understanding the world.