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

::::: {#visualization-pearsons-correlation-coefficient .section .level2}
## Visualization & Pearson's correlation coefficient {.anchored anchor-id="visualization-pearsons-correlation-coefficient"}

The
[`30DayChartChallenge`](https://nightingaledvs.com/the-30daychartchallenge-year-three/)
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. In
these datasets, the mean and the standard deviation of
![](https://latex.codecogs.com/png.latex?x) and
![](https://latex.codecogs.com/png.latex?y) remain almost the same, but
the distribution of observation pairs goes through obvious drastic
changes.

:::: {.cell messages="false"}
Code

::: {#cb1 .sourceCode .cell-code style="background: #f1f3f5;"}
``` {.sourceCode .numberSource .r .number-lines .code-with-copy}
## -------------------------------------- ##
## Day 19: Dinosaurs; 30DayChartChallenge ##
## -------------------------------------- ##
## Loading libs                           ##
library(datasauRus)                       ##
library(tidyverse)                        ##
library(gganimate)                        ##                                                    
library(showtext)                         ##
## -------------------------------------- ##

# Setting custom theme for ggplot2 graphics

clrs <- c( # Creating custom color palette
  "#e5b858", #  yellow
  "#B72025", #  red
  "#7C225C", #  purple
  "#d3d6d9", #  dark gray
  "#f9f9f9", #  light gray
  "#394DAA") #  blue

# Import Fonts (google name, R name)
font_add_google("Source Code Pro","source_code")
font_add_google("Montserrat","mont")
showtext_auto() # enable showtext font rendering

theme_blue <- function() {
  theme_minimal(base_family = "mont") +
  theme(
    plot.title = element_text(family = "mont", face = "bold", size = rel(1.35)),
    plot.subtitle = element_text(family = "mont", colour = "royalblue", face = "plain", size = rel(1)),
    plot.background = element_rect(fill = clrs[5], colour = clrs[5]),
    panel.border = element_blank(),
    panel.background = element_rect(fill = clrs[5]),
    panel.grid.major.x = element_line(colour = clrs[6], linetype = 3, linewidth = .35),
    panel.grid.minor.x = element_blank(),
    panel.grid.major.y =  element_line(colour = clrs[6], linetype = 3, linewidth = .35),
    panel.grid.minor.y = element_blank(),
    # modify text, axis and colour 4) and 5)
    axis.text = element_text(colour = clrs[6], face = "plain", family = "mont"),
    axis.title = element_text(colour = clrs[6], family = "mont"),
    axis.ticks = element_line(colour = clrs[6]),
    # legend at the bottom 6)
    legend.position = "none"
  )
}

theme_set(theme_blue())

ggplot2::update_geom_defaults("label", list(family = "mont", fontface = "bold"))
ggplot2::update_geom_defaults("text", list(family = "mont", fontface = "plain"))


# Checking min/max for axis transform
datasaurus <- datasaurus_dozen
summary(datasaurus)

dino <- ggplot(datasaurus, aes(x = x, y = y))+
  geom_point(size = 3, alpha = .65, 
             colour = clrs[3]) +
  labs(x = NULL,y = NULL,
       title = "Day 19 of 30 Day Chart Challenge",
       subtitle = "The T-rex",
       caption = "Always check your data graphically") +
  theme_blue() +
  transition_states(states = dataset,
                    transition_length = 2,
                    state_length = 1,
                    wrap = TRUE) +
  ease_aes("linear")

animate(dino, duration = 15, fps = 24, height = 680, width = 720,
        renderer = gifski_renderer())

anim_save(filename = "dino.gif",
          path = here::here("blog","2024","04","dinosaurs","img"))
```
:::
::::
:::::

::: {#the-animated-data .section .level2}
## The Animated Data {.anchored anchor-id="the-animated-data"}

![Datasaurus Day 19 Chart Challenge
2024](https://www.jpmonteagudo.com/blog/2024/04/dinosaurs/img/dino.gif)
:::

:::::: {#measures-of-central-tendency .section .level2}
## Measures of Central Tendency {.anchored anchor-id="measures-of-central-tendency"}

::::: {.cell .tbl-cap-location-top tbl-colwidths="[50,50]"}
Code

::: {#cb2 .sourceCode .cell-code cap-location="top" style="background: #f1f3f5;"}
``` {.sourceCode .numberSource .r .number-lines .code-with-copy}
library(datasauRus) 
library(knitr)
library(tidyverse)

datasaurus <- datasaurus_dozen
group_datasaurus <- datasaurus %>%
  group_by(dataset) %>% 
  summarize(avg_x = round(mean(x),2), 
            stdev_x = round(sd(x),2), 
            avg_y = round(mean(y),2), 
            stdev_y = round(sd(y),2))
knitr::kable(group_datasaurus,
             col.names = c('Data', 'Mean(x)','SD(x)','Mean(y)','SD(y)'))
```
:::

::: {.cell-output-display}
| Data       | Mean(x) | SD(x) | Mean(y) | SD(y) |
|:-----------|--------:|------:|--------:|------:|
| away       |   54.27 | 16.77 |   47.83 | 26.94 |
| bullseye   |   54.27 | 16.77 |   47.83 | 26.94 |
| circle     |   54.27 | 16.76 |   47.84 | 26.93 |
| dino       |   54.26 | 16.77 |   47.83 | 26.94 |
| dots       |   54.26 | 16.77 |   47.84 | 26.93 |
| h_lines    |   54.26 | 16.77 |   47.83 | 26.94 |
| high_lines |   54.27 | 16.77 |   47.84 | 26.94 |
| slant_down |   54.27 | 16.77 |   47.84 | 26.94 |
| slant_up   |   54.27 | 16.77 |   47.83 | 26.94 |
| star       |   54.27 | 16.77 |   47.84 | 26.93 |
| v_lines    |   54.27 | 16.77 |   47.84 | 26.94 |
| wide_lines |   54.27 | 16.77 |   47.83 | 26.94 |
| x_shape    |   54.26 | 16.77 |   47.84 | 26.93 |

Mean & Standard Deviation of *x* and *y*
:::
:::::
::::::

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

<div>

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

::: {#ref-monteagudo2024 .csl-entry .quarto-appendix-citeas}
Monteagudo, JP. 2024. "Animating the Datasaurus Dataset as Part of the
\*30 Day Chart Challenge\*." April 19, 2024.
<https://doi.org/10.59350/wx5k1-ajc38>.
:::

</div>
::::::
:::::::
