The value of fame during and after life
Today I want to reflect on the following quote from The Meditations:
People who are excited by posthumous fame forget that the people who remember them will soon die too. And those after them in turn. Until their memory, passed from one to another like a candle flame, gutters and goes out. But suppose that those who remembered you were immortal and your memory undying. What good would it do you? And I don't just mean when you're dead, but in your own lifetime. What use is praise, except to make your lifestyle a little more comfortable?
"You're out of step—neglecting the gifts of nature to hand on someone's words in the future."
Marcus was the most powerful person on the planet with the most prestigious job, Emperor. It doesn't get much better than that. But there's probably no amount of fame or social status that will satisfy us. Something for me to keep in mind.
Articles
Personal notes I've written over the years.
- When does the Binomial become approximately Normal
- Gambler's ruin problem
- The t-distribution becomes Normal as n increases
- Marcus Aurelius on death
- Proof of the Central Limit Theorem
- Proof of the Strong Law of Large Numbers
- Deriving Multiple Linear Regression
- Safety stock formula derivation
- Derivation of the Normal Distribution
- Comparing means of Normal populations
- Concentrate like a Roman
- How to read a Regression summary in R
- Notes on Expected Value
- How to read an ANOVA summary in R
- The time I lost faith in Expected Value
- Notes on Weighted Linear Regression
- How information can update Conditional Probability
- Coupon collecting singeltons with equal probability
- Coupon collecting with n pulls and different probabilities
- Coupon collecting with different probabilities
- Coupon collecting with equal probability
- Adding Independent Normals Is Normal
- The value of fame during and after life
- Notes on the Beta Distribution
- Notes on the Gamma distribution
- Notes on Conditioning
- Notes on Independence
- A part of society
- Conditional Expectation and Prediction
- Notes on Covariance
- Deriving Simple Linear Regression
- Nature of the body
- Set Theory Basics
- Polynomial Regression
- The Negative Hyper Geometric RV
- Notes on the MVN
- Deriving the Cauchy density function
- Exponential and Geometric relationship
- Joint Distribution of Functions of RVs
- Order Statistics
- The Sample Mean and Sample Variance
- Probability that one RV is greater than another
- St Petersburg Paradox
- Drunk guy by a cliff
- The things that happen to us