This is a part of our initiative (Bharath’s Reading list) to document all articles that we keep sharing through our reading list. This blog post contains articles shared in the last one week. The articles are from a wide variety of topics and will also be updated inside the individual topic list as well.
Keep this link open in a browser. Click on individual articles available below. Read them to improve your CAT VARC Preparation in the long run. There are no shortcuts when it comes to CAT VARC preparation. Persistence is the key to getting a great VARC Percentile in CAT. All the articles that I shared in the last one week are listed below date-wise.
14-12-2020
“My Experiments with Matrimony
My matrimonial journey started on the same day I hit 27. That’s the autumn-age of life, not just because it’s beautiful, but also, that’s when your hair starts falling just like the leaves. On the first day of my autumn, my parents tried to surprise me by setting up a matrimonial profile as a birthday gift.”
https://bit.ly/3a7BkkL
15-12-2020
“In Nyāya philosophy only some debates are worth having
In premodern India, debates were entertainment in courtly settings, a sport for profiteers and clever men who enjoyed a quick turn of phrase or put-down. Successful debaters gained followers, fame, even wealth.”
http://bit.ly/2JY5sVn
16-12-2020
https://online.2iim.com/CAT-2020-Response-Sheet-Analysis.shtml
Hello folks!
Post the release of the CAT 2020 Response Sheets, we put out a 2IIM Score Calculator to help candidates breeze past the tedious counting, nervousness, and recounting.
The data that we collected from the entries gave us ample opportunities to dive deep into crunching this data (and also have some fun!)
A small note: We decided to make the data available to everyone to promote transparency, and have also made it a point to anonymize the data.
The nature of this endeavor was purely analysis-driven and NOT a Trojan Horse sent out to collect personal data from the entries.
What is the nature of our data?
Can we make any direct percentile inferences from this data?
How do the slots fare against each other?
Which section was the toughest? How much does it differ between slots?
What is the impact of normalisation across slots?
Most importantly, how do the sectional cutoffs and percentile ranges look like?
And more. Read on to delve into some number crunching and data interpretation (the charts that we did not see in CAT 2020 :P)
17-12-2020
“Secret Amazon Reports Expose the Company’s Surveillance of Labor and Environmental Groups”
http://bit.ly/34nmJhA
18-12-2020
“The extra materials and energy involved in manufacturing a lithium-ion battery mean that, at present, the carbon emissions associated with producing an electric car are higher than those for a vehicle running on petrol or diesel – by as much as 38%, according to some calculations. Until the electricity in national grids is entirely renewable, recharging the battery will involve a degree of dependence on coal or gas-fired power stations.”
http://bit.ly/37t0EA7
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