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# Communicate {#sec-communicate-intro .unnumbered}
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```{r}
#| results: "asis"
#| echo: false
source("_common.R")
```
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So far, you've learned the tools to get your data into R, tidy it into a form convenient for analysis, and then understand your data through transformation, and visualization.
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However, it doesn't matter how great your analysis is unless you can explain it to others: you need to **communicate** your results.
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```{r}
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#| label: fig-ds-communicate
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#| echo: false
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#| fig-cap: |
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#| Communication is the final part of the data science process; if you
#| can't communicate your results to other humans, it doesn't matter how
#| great your analysis is.
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#| fig-alt: |
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#| A diagram displaying the data science cycle with
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#| communicate highlighed in blue.
#| out.width: NULL
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knitr::include_graphics("diagrams/data-science/communicate.png", dpi = 270)
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```
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Communication is the theme of the following two chapters:
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- In @sec-quarto, you will learn about Quarto, a tool for integrating prose, code, and results.
You can use Quarto for analyst-to-analyst communication as well as analyst-to-decision-maker communication.
Thanks to the power of Quarto formats, you can even use the same document for both purposes.
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- In @sec-quarto-formats, you'll learn a little about the many other varieties of outputs you can produce using Quarto, including dashboards, websites, and books.
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These chapters focus mostly on the technical mechanics of communication, not the really hard problems of communicating your thoughts to other humans.
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However, there are lot of other great books about communication, which we'll point you to at the end of each chapter.