data_science_in_julia_for_hackers
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unbalancedparentheses
Suggestions for Chapter 5
Chapter 5
This chapter has some questions that help readers to be engaged with critical steps not usually decoded, congrats!
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[x] Introduce section 5.2 “Modelling and performing probabilistic experiments” After “So how do we model the outcomes of flipping a coin?”
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[x] Replace: to define probability models and solving them automatically. By: to define probability models and solve them automatically.
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[x] Replace: when using this tools By: when using these tools
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[x] Replace: the Bernoulli distribution gives us the probability of obtaining different number of heads (and tails too, if we know the total number of trials and the number of times we got heads, we know that the remaining number of times we got tails). By: the Bernoulli distribution gives us the probability of obtaining a different number of heads (and tails too, if we know the total number of trials and the number of times we got heads, we know the remaining number of times we got tails).
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[x] Replace: xlabel="Succeses" By: xlabel="Successes"
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[x] Replace: The argument that this function will recieve is the data from our experiment. By: The argument that this function will receive is the data from our experiment.
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[x] Replace: We see that some values near 0 and 1 have still high probability for the model By: We see that some values near 0 and 1 still have high probability for the model
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[ ] In the last image, the title may be shorter to avoid overlapping (or charts be bigger). It would be great to standardize the way of presenting charts across chapters.
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[ ] The MCMC has to be introduced in a sequence or a box, for instance: -- What is a Markov chain or process? What for? -- What is a Monte Carlo simulation? When is it used? -- What does MCMC mean? Why do you use it here?
