index.Rmd

---
title: "Statistics Notebook"
---

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This page, and all pages of this notebook, are meant to be customized to become a useful *Guide to Statistical Analysis* in R for your *current* and *future* self. 

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To begin customizing, [download](https://github.com/saundersg/Statistics-Notebook) your own copy of the book <span style="font-size:.8em;">(if you haven't already)</span>. Please note the [GNU General Public License](https://choosealicense.com/licenses/gpl-3.0/) when downloading. You are free to delete this commentary in your own copy of the notebook.

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## Table of Contents 


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## {.tabset .tabset-fade}

### Hide 

### Show Notes

<!-- This is a great place to add general notes, then "Knit" the file to have your notes show up in your Statistics-Notebook. --------------- -->




Wow! I typed some words. Some <span style="color:blue;">blue words</span>, some <span style="background-color:yellow;">highlighted words</span>, some <span style="font-size:2em;">big words</span>.

Make a link to a meaningful page of the Statistics-Notebook: [Customization Help](RMarkdownHints.html) <- Read through this page!

Or to a page on the internet: [R Colors](http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf)



```{r}
mean(airquality$Temp)
```













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##

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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantY.png" width=35px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest. This would be like "heights" of BYU-Idaho students.</span>
</div>

## One Quantitative Response Variable Y {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->



Add your own notes about graphics to use for this type of data here.





<a href="GraphicalSummaries.html#histogram">
  <img class="myhover" src="./Images/histogram.png" alt="Histogram" title="Histogram">
</a>
<a href="GraphicalSummaries.html#dot-plots">
  <img class="myhover" src="./Images/dotplotsingle.png" alt="Dot Plot" title="Dot Plot">
</a>
<a href="GraphicalSummaries.html#boxplots">
  <img class="myhover" src="./Images/boxplotsingle.png" alt="Boxplot" title="Boxplot">
</a>



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### Tests
<div style="padding-left:125px;color:lightgray;">
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Add your own notes about appropriate inferential procedures for this type of data here.


















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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantYQualXg2.png" width=59px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest. This would be like "heights" of BYU-Idaho students. X is a qualitative (categorical) variable of interest like "gender" that has just two groups "A" and "B". So this logo represents situtations where we would want to compare heights of male (group A) and female (group B) students.</span>
</div>

## Quantitative Y | Categorical X (2 Groups) {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.













<a href="GraphicalSummaries.html#boxplots">
  <img class="myhover" src="./Images/boxplot.png" alt="Side-by-side Boxplots" title="Side-by-side Boxplots">
</a>
<a href="GraphicalSummaries.html#dot-plots">
  <img class="myhover" src="./Images/dotplotdouble.png" alt="Dot Plot" title="Side-by-side Dot Plots">
</a>



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### Tests
<div style="padding-left:125px;color:lightgray;">
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##
<div style="clear:both;"></div>

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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantYQualXg3plus.png" width=59px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest, like "heights" of BYU-Idaho students. X is a categorical (qualitative) variable like which Math 221 you took, 221A, 221B, or 221C. In other words, X has three or more groups. So "Classrank" could be X, with groups "Freshman", "Sophomore", "Junior", and "Senior".</span>
</div>

## Quantitative Y | Categorical X (3+ Groups) {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.












<a href="GraphicalSummaries.html#boxplots">
  <img class="myhover" src="./Images/boxplotthree.png" alt="Side-by-side Boxplots" title="Side-by-side Boxplots 3+ Groups">
</a>
<a href="GraphicalSummaries.html#dot-plots">
  <img class="myhover" src="./Images/dotplottriple.png" alt="Side-by-side Dot Plots" title="Side-by-side Dot Plots 3+ Groups">
</a>

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</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






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#
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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantYMultQualX.png" width=80px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest, like "heights" of BYU-Idaho students. X1 is a categorical (qualitative) variable like gender, with levels "boy" and "girl." X2 is another categorical (qualitative) variable like "Classrank" with levels "Freshman", "Sophomore", and "Junior". Of course, both X1 and X2 can have as many levels as you want to work with, but must have at least two levels each.</span>
</div>

## Quantitative Y | Multiple Categorical X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.












<a href="GraphicalSummaries.html#boxplots">
  <img class="myhover" src="./Images/boxplotthree.png" alt="Side-by-side Boxplots" title="Side-by-side Boxplots 3+ Groups">
</a>
<a href="GraphicalSummaries.html#dot-plots">
  <img class="myhover" src="./Images/dotplottriple.png" alt="Side-by-side Dot Plots" title="Side-by-side Dot Plots 3+ Groups">
</a>

<!--- End of Add content area.  ------------------>
</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

#
<div style="clear:both;"></div>

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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantYQuantX.png" width=59px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest, like "height". X is another single quantitative variable of interest, like "shoe-size". This would imply we are using "shoe-size" (X) to explain "height" (Y).</span>
</div>

## Quantitative Y | Quantitative X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.









<a href="GraphicalSummaries.html#scatterplots">
  <img class="myhover" src="./Images/scatterplot.png" alt="Scatterplot" title="Scatterplot">
</a>

<!--- End of Add content area.  ------------------>
</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

#
<div style="clear:both;"></div>

----

<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QuantYMultX.png" width=100px;>
  <span class="tooltipimagetext">Y is a single quantitative variable of interest, like height. While we could use an X1 of "shoe-size" to explain height, we might also want to use a second x-variable, X2, like "gender" to help explain height. Further x-variables could also be used.</span>
</div>

## Quantitative Y | Multiple X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.









<a href="GraphicalSummaries.html#scatterplots">
  <img class="myhover" src="./Images/scatterplotmany.png" alt="Scatterplot" title="Scatterplot with Color and Sizing">
</a>

<!--- End of Add content area.  ------------------>
</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

#
<div style="clear:both;"></div>

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<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/BinomYQuantX.png" width=59px;>
  <span class="tooltipimagetext">Y is a single categorical (qualitative) variable of interest where 1 (success) or 0 (failure) are the only possible values for Y. This would be like "getting an A in Math 325" where 1 means you got an A and 0 means you didn't. We might use an explanatory variable X of "height" to see if taller students are more likely to get an A in Math 325 than shorter students. (They aren't, if you were wondering.)</span>
</div>

## Binomial Y | Quantitative X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.







<a href="GraphicalSummaries.html#scatterplots">
  <img class="myhover" src="./Images/scatterplotbinomY.png" alt="Scatterplot with Binomial Y" title="Scatterplot with Binomial Y">
</a>

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</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

#
<div style="clear:both;"></div>

----

<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/BinomYMultX.png" width=100px;>
  <span class="tooltipimagetext">Y is a single categorical (qualitative) variable of interest where 1 (success) or 0 (failure) are the only possible values for Y. This would be like "getting an A in Math 325" where 1 means you got an A and 0 means you didn't. We might use an explanatory variable X1 of "height" and a second explanatory variable X2 of "gender" to try to predict whether or not a student will get an A in Math 325.</span>
</div>

## Binomial Y | Multiple X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.







<a href="GraphicalSummaries.html#scatterplots">
  <img class="myhover" src="./Images/scatterplotbinomYmult.png" alt="Scatterplot with Binomial Y" title="Scatterplot with Binomial Y, including coloring and shading">
</a>

<!--- End of Add content area.  ------------------>
</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

#
<div style="clear:both;"></div>

----

<div style="float:left;width:125px;" align=center class="tooltipimage">
<img src="./Images/QualYQualX.png" width=59px;>
  <span class="tooltipimagetext">Y is a single categorical variable of interest, like gender. X is another categorical variable of interest, like "hair color". This type of data would help us understand if men or women are more likely to have certain hair colors than the other gender.</span>
</div>

## Categorical Y | Categorical X {.tabset .tabset-pills}

### Graphics
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about graphics to use for this type of data here.






<a href="GraphicalSummaries.html#bar-charts">
  <img class="myhover" src="./Images/barplot.png" alt="Bar Chart" title="Bar Chart">
</a>

<!--- End of Add content area.  ------------------>
</div>

### Tests
<div style="padding-left:125px;color:lightgray;">
<!-- Add your customizations in the area below: -->

Add your own notes about appropriate inferential procedures for this type of data here.






<!--- End of Add content area.  ------------------>
</div>

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