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[prob_dist] Editorial Comments #402

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@HumphreyYang

Description

@HumphreyYang

Feedback from @longye-tian (Thanks!)

Code

  • Remove redundant code in the Poisson distribution simulation

Content

  • Give some motivations to use different probability distributions
  • "One simple example is the uniform distribution, where $p(x_i) = 1/n$ for all $i$ "- > "One simple example is the uniform distribution, where $p(x_i) = 1/n$ for all $n$"
  • Add some explanations to randint in scipy (by adding a link).
  • Unify : after the sentence before the code
  • Unify "PDF" to "PMF" in discrete cases.
  • add labels for x and y axis.
  • The CDF jumps up by $p(x_i)$ and $x_i$.
  • Update Bernoulli distribution section (@longye-tian) [prob_dist] Bernoulli distribution section - editorial suggestions #403.
  • the number of successes in $n$
    independent trials with success probability $\theta$ -> the probability of successes in $n$
    independent trials with success probability $\theta$.
  • "Continuous distributions are represented by a density function" -> "Continuous distributions are represented by a probability density function (PDF)"
  • "the set of all numbers" -> "the set of all real numbers"
  • $a \leq b$ -> $a < b$ or change the probability distribution functions.
  • "We can obtain the moments, PDF and CDF of the normal density as follows" -> "We can obtain the moments, PDF and CDF of the log-normal density as follows"

Comments by @mbek0605:

Content

  • Bernoulli is a distribution for only two outcomes - make that more clear
  • Economic examples for the distributions(?) (Poisson, for example, - useful for calculating the odds of a certain event, or a link to another lecture where it is used / wikipedia)
  • Comparison between distributions
  • Use case in economics and examples
  • We could have the empirical distributions first and then go on to the theoretical distributions (switch the order of the lectures)
  • Idea: summary table at the end (mean, variance, cdf and pdf of each one)
  • "The the expectation of Poisson distribution" -> "The expectation of Poisson distribution"

Code

  • label x,y axis in figures
  • add mystnb figures wrappers

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