lecture-python-intro
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[prob_dist] Editorial Comments
Feedback from @longye-tian (Thanks!)
Code
- [ ] Remove redundant code in the Poisson distribution simulation
Content
- [ ] Give some motivations to use different probability distributions
- [x] "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
randintinscipy(by adding a link). - [x] Unify
:after the sentence before the code - [x] Unify "PDF" to "PMF" in discrete cases.
- [ ] add labels for x and y axis.
- [x] The CDF jumps up by $p(x_i)$ and $x_i$.
- [x] Update Bernoulli distribution section (@longye-tian) #403.
- [x] the number of successes in $n$ independent trials with success probability $\theta$ -> the probability of successes in $n$ independent trials with success probability $\theta$.
- [x] "Continuous distributions are represented by a density function" -> "Continuous distributions are represented by a probability density function (PDF)"
- [x] "the set of all numbers" -> "the set of all real numbers"
- [x] $a \leq b$ -> $a < b$ or change the probability distribution functions.
- [x] "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