JP Monteagudo

Memorization   “The main reason to memorize the Bible is not to accumulate more data in our brains. It’s a way for us to enjoy God” - Andy Naselli  I’ve started to memorize big chunks of the Bible with a group of men at church, and this has been both, challenging and amazing. Somehow, I feel more ready for the day when I bring scripture to the forefront of my mind.

john 1:1 - 18

Lissajous Curves   Lissajous curves are created by plotting two oscillations on perpendicular axes  and ​​​. These oscillations, represented by sinusoidal functions, intersect to create different patterns. When the ratio of these frequencies is equal to — the oscillations are equally phased— the curve is a straight line.

Beautiful movement—the music and beauty of Lissajous(Liss–uh–joo) curves

Visualization &amp; Pearson’s correlation coefficient   The 30DayChartChallenge is a data visualization community that hosts daily challenges for April. Today’s challenge involves dinosaurs. I used the Datasaurus package to create an animated visualization to demonstrate the importance of graphing data, and the effects of outliers on statistical properties.

Animating the Datasaurus dataset as part of the 30 Day Chart Challenge

RQ: What exactly is the CLT and what’s the deal with n  30?   CLT - mathematical definition and simple terms definition  How we use CLT  How to know when empirical distribution converges to normal distribution? How did we come up with n $ $ 30?  Cohen (1991) Taught that at least 30 observations were needed to use critical-ratio approach used in t-tables when comparing groups.

“{Can I have the CLT, please– a straightforward explanation of the Central Limit Theorem and the magic (n )}”

monthly changes in her circle orb   Tip  If you’re wondering where I’m getting my titles and headings, they come from Shakespeare’s sonnets. The moon has always fascinated me. Eversince I was a child, I was entranced by it; her constant pursuit everywhere I went and her sneaky tactics during the day. This year, before the solar eclipse, I decided to do a little digging and replicate one algorithm used to determine the phases of the moon.

swear not by the moon, the fickle moon

TL; DR:   Don’t be an absolutist– use relative paths. Use the here package instead of setwd() or getwd() to increase reproducibility and avoid wasting your and other people’s time.

Don’t be an absolutist. Use the here package for reproducible workflows

Quantile Beta Regression   The quantile beta regression model discussed in the 2021 paper by Running Code   When you click the
<strong>
 Render
</strong>
button a document will be generated that includes both content and the output of embedded code.

A parametric quantile beta regression for modeling case fatality rates of COVID-19. Building models using the betareg and RBE3 packages

not so quickly! Recently, I become intrigued by game theory algorithms, not because I absolutely love playing games, but because it offers a quantifiable, systematic way to understand human relationships. I find the certainty of science and systematization reassuring to some degree so when I learned about this game called “the prisoner’ dilemma”, I thought it would fun to experiment and figure out the answer to this classic scenario.

the iterated prisoners’ dilemma

JP's blog

::: {#rq-what-exactly-is-the-clt-and-whats-the-deal-with-n-geqslant-30 .section .level2}
## RQ: What exactly is the CLT and what's the deal with n ![](https://latex.codecogs.com/png.latex?%20%5Cgeqslant%20) 30? {#rq-what-exactly-is-the-clt-and-whats-the-deal-with-n-30 .anchored anchor-id="rq-what-exactly-is-the-clt-and-whats-the-deal-with-n-geqslant-30"}

- CLT - mathematical definition and simple terms definition

- How we use CLT

- How to know when empirical distribution converges to normal
  distribution?

- How did we come up with n \$ \$ 30?

  - Cohen (1991) Taught that at least 30 observations were needed to use
    critical-ratio approach used in t-tables when comparing groups. If
    sample size smaller than 30, then students would be forced to
    "small" sample statistics.

    > It wasn't until some years later that I discovered (mind you, not
    > invented) power analysis, one of whose fruits was the revelation
    > that for a two-independent-group-mean comparison with n = 30 per
    > group at the sanctified two-tailed .05 level, the probability that
    > a medium-sized effect would be labeled as significant by the most
    > modern methods (a t-test) was only .47. Thus, it was approximately
    > a coin flip whether one would get a significant result, even
    > though, in reality, the effect size was meaningful.

    - Simply a rule of thumb that allowed students to use critical
      t--tables. These tables could only span 30 lines to fit in one
      page. Fisher created the t--table and only went up to n = 30
      (Fisher's *Statistical Methods for Research Workers* (1925))
    - Sample size at least 30 so that the error variance between
      t--t-distribution and theoretical normal distribution is .25 or
      less from df = 30 up to infinity.
    - When data is severely skewed neither the t--test nor the
      permutation test have much power (are not robust) to correctly
      identify a statistically significance difference in means between
      too highly skewed distributions. Even if your data contained tens
      of thousands of observations, the t--test may not recognize a
      statistically significance difference in means. The distribution
      of the data and the number of observations need to be considered
      when deciding whether the t--test is meaningful and accurate,
      sometimes thousands of observations may be needed.

  ## Solution {#solution .anchored}

  - Use power analysis to determine the sample size needed to obtain
    statistically significant results using your desired
    ![](https://latex.codecogs.com/png.latex?%5Calpha),
    ![](https://latex.codecogs.com/png.latex?%5Cbeta) and effect size
    measure. This way, you don't have to assume
:::

::: {#quarto-appendix .default}
::: {#quarto-citation .section .quarto-appendix-contents}
## Citation {#citation .anchored .quarto-appendix-heading}

<div>

::: {.quarto-appendix-secondary-label}
BibTeX citation:
:::

``` {.sourceCode .code-with-copy .quarto-appendix-bibtex}
@online{monteagudo2024,
  author = {Monteagudo, JP},
  title = {“{\{Can} {I} Have the {CLT,} Please– a Straightforward
    Explanation of the {Central} {Limit} {Theorem} and the Magic
    \textbackslash(n \textbackslash Geqslant 30\textbackslash)\}”},
  date = {2024-03-06},
  url = {https://www.jpmonteagudo.com/blog/2024/02/clt},
  langid = {en}
}
```

::: {.quarto-appendix-secondary-label}
For attribution, please cite this work as:
:::

::: {#ref-monteagudo2024 .csl-entry .quarto-appendix-citeas}
Monteagudo, JP. 2024. "'{Can I Have the CLT, Please-- a Straightforward
Explanation of the Central Limit Theorem and the Magic \\n \Geqslant
30\\}'." March 6, 2024. <https://www.jpmonteagudo.com/blog/2024/02/clt>.
:::

</div>
:::
:::
