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Imrpoves intro to visualization chapter.

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Garrett 2016-04-01 16:44:38 -04:00
parent 0557e58ca0
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visualize.Rmd
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@ -2,7 +2,7 @@
> "The simple graph has brought more information to the data analyst’s mind than any other device."---John Tukey
Visualization makes data decipherable. Consider what it is like to study a table of raw data. You can examine a couple of values at a time, but you cannot attend to many values at once. The data overloads your attention span, which makes it hard to spot patterns in the data. See this for yourself; can you spot the striking relationship between $X$ and $Y$ in the table below?
If you are like most humans, your brain is not designed to work with raw data. Your brain can only attend to a few values at a time, which makes it difficult to discover patterns in raw data, like in the table below. Can you spot the striking relationship between $X$ and $Y$?
```{r data, echo=FALSE}
x <- rep(seq(0.2, 1.8, length = 5), 2) + runif(10, -0.15, 0.15)
@ -14,7 +14,9 @@ order <- sample(1:10)
knitr::kable(round(data.frame(X = X[order], Y = Y[order]), 2))
```
Raw data is difficult to comprehend, but visualized data is easy to understand. Once you plot your data, you can see the relationships between data points---instantly. For example, the graph below shows the same data as above. Here, the relationship between the points is obvious.
While you may stumble over raw data, you can easily process visual information. Within your mind is a visual processing system that has been fine-tuned by thousands of years of evolution.
As a result, the quickest way to understand your data is to visualize it. Once you plot your data, you can instantly see the relationships between values. Here, we see that the values above fall on a circle.
```{r echo=FALSE, dependson=data}
ggplot2::qplot(X, Y) + ggplot2::coord_fixed(ylim = c(-2.5, 2.5), xlim = c(-2.5, 2.5))