An Introduction to [ comment ] and RStudio for Educational Researchers

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.title[
# An Introduction to <svg viewBox="0 0 581 512" xmlns="http://www.w3.org/2000/svg" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#384CB7;"> [ comment ] <path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z" /></svg>and RStudio for Educational Researchers
]
.subtitle[
## Descriptive and Inferential Statistics: Graphics
]
.author[
### Jorge Sinval
]
.date[
### 2025-11-18
]

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# 2. Descriptive Statistics and Graphics

---

# 2.7 Graphical representations

>Visual representation of descriptive and association statistics

**Advantages**: easy acquisition of information -visual memory

**Disadvantages**: undemanding, and can be misleading

.pull-left[

There are many plots...

![:scale 100%](data:image/png;base64,#assets/img/cars_ggplot2_hex.png)
]

.pull-right[

But <svg viewBox="0 0 581 512" xmlns="http://www.w3.org/2000/svg" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#384CB7;"> [ comment ] <path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"></path></svg>'s are more fun!

![:scale 100%](data:image/png;base64,#assets/gif/traplota.gif)

]

---
exclude: true
# ... and more plots!

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</center>

---

# Plots with `ggplot2`

- Hadley Wickham's [Doctoral thesis](http://had.co.nz/thesis/practical-tools-hadley-wickham.pdf)🎓.
 
- Based on Leland Wilkinson's *grammar of graphics* 📚.

> A plot is a visual representation of data that uses aesthetic attributes (position, color, shape, size, ...) of geometric shapes (points, lines, bars, ...).

.footnote[
👩‍🎓 Wickham, H. A. (2008). Practical tools for exploring data and models [Doctoral thesis, Iowa State University]. https://lib.dr.iastate.edu/rtd/15639

📚 Wilkinson, L. (2005). _The grammar of graphics_ (2nd ed.). Springer. https://doi.org/10.1007/0-387-28695-0

]

---

# Data visualization with `ggplot2`

- Based on this definition, Hadley developed the *layered grammar of graphics*: each graphic element can be represented by a layer, and a graphic will be the overlay of these layers.

.pull-left[
<center>
<img src="assets/img/layers.png" width = 60%>
</center>

]

.pull-right[

<center>
![:scale 50%](data:image/png;base64,#assets/img/ggplot2_hex.png) 
</center>
]

However, not only from `ggplot2` do graphics live in <svg viewBox="0 0 581 512" xmlns="http://www.w3.org/2000/svg" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#384CB7;"> [ comment ] <path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"></path></svg>, graphics can also be produced with the `base` package...

---

# Boxplot

.pull-left[

]

.pull-right[

One of the most informative graphical representations. 💡

The height of the box corresponds to the `\(IQR=Q_3-Q_1\)`.

However, the frequency of its use is less than expected.

Useful for ordinal and quantitative variables.

]

--
.footnote[

💡 Very suitable for identifying .orange[outliers.]

]

---

# Alternatives

Other identical forms of representation (e.g. .orange[dot plots], and .orange[Highest Density Region (HDR) box Plots]... [among others](http://datavizcatalogue.com/blog/box-plot-variations/ "See here other possibilities") )

---

# Histogram

.pull-left[

</center>

]

.pull-right[

Variables on the abscissa (xx) axis can be continuous (using classes built with the Sturges rule📜) or discrete.

Frequencies on the ordinate (yy) can be relative or absolute.

]

.footnote[

📜 Sturges, H. A. (1926). The choice of a class interval. _Journal of the American Statistical Association, 21_(153), 65–66. [https://doi.org/10.1080/01621459.1926.10502161](https://doi.org/10.1080/01621459.1926.10502161)

]

---

# Bar graph

.pull-left[

</center>

]

.pull-right[

The length of the bars on the y-axis (yy) is proportional to the dimension of the categories of the qualitative variable, represented on the abscissa axis (xx):

Frequencies on the ordinate (yy) axes can be absolute `\((n_i)\)` or relative `\((f_i)\)`.

]

---

# Error-bar graph

.pull-left[
 
 
<center>

</center>

]

.pull-right[

The bar represents `\(\bar x\)`.

The "whiskers" represents the `\(SEM\)` (or `\(S’\)`).

]

---

# Circle chart

.pull-left[

</center>

]

.pull-right[

Circular representation of absolute `\((n_i)\)` or relative `\((f_i)\)` frequencies.

]

---

# Scatter plot

.pull-left[

</center>

]

.pull-right[

Useful to illustrate bivariate relationships between variables.

Two quantitative variables are needed.

]

---

# Summary

The graphical analysis depends on the information that the variables present, i.e. on the .orange[measurement scale].

| Measurement scale | Graphical representation |
|------------------|-----------------------|
| Qualitative: Nominal | Bar graph Circle chart |
| Qualitative: Ordinal| Bar graph Circle chart Boxplot |
| Quantitative: Interval Ratio| Error-bar graph Boxplot Histogram Scatter plot|

---

# Creativity

.pull-left[
Make use of creativity without losing rigor.

Remembering that...

_You can put lipstick on a pig..._

]

.pull-right[

![:scale 80%](data:image/png;base64,#assets/img/lipstick_pig.jpg)

</center>

]

but it’s still a pig.

</center>

---

# Creativity

![:scale 50%](data:image/png;base64,#assets/gif/happyaccidents.gif)
</center>

---

# Creativity

---
class: center, bottom, inverse

# More info

Slides created with the <svg viewBox="0 0 581 512" xmlns="http://www.w3.org/2000/svg" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#384CB7;"> [ comment ] <path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"></path></svg> package [`xaringan`](https://github.com/yihui/xaringan).

Practice is the best strategy for learning.

_In God we trust, all others bring data_

Edwards Deming

THE END

---
class: center, bottom, inverse

![:scale 50%](data:image/png;base64,#assets/gif/the_end.gif)