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<!DOCTYPE html>
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<title>Chapter 10 Inference for Regression | Modern Biological Data Analysis</title>
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<li class="chapter" data-level="1.4.3" data-path="1-getting-started.html"><a href="1-getting-started.html#exploredataframes"><i class="fa fa-check"></i><b>1.4.3</b> Exploring data frames</a></li>
<li class="chapter" data-level="1.4.4" data-path="1-getting-started.html"><a href="1-getting-started.html#identification-vs-measurement-variables"><i class="fa fa-check"></i><b>1.4.4</b> Identification and measurement variables</a></li>
<li class="chapter" data-level="1.4.5" data-path="1-getting-started.html"><a href="1-getting-started.html#help-files"><i class="fa fa-check"></i><b>1.4.5</b> Help files</a></li>
</ul></li>
<li class="chapter" data-level="1.5" data-path="1-getting-started.html"><a href="1-getting-started.html#conclusion"><i class="fa fa-check"></i><b>1.5</b> Conclusion</a>
<ul>
<li class="chapter" data-level="1.5.1" data-path="1-getting-started.html"><a href="1-getting-started.html#additional-resources"><i class="fa fa-check"></i><b>1.5.1</b> Additional resources</a></li>
<li class="chapter" data-level="1.5.2" data-path="1-getting-started.html"><a href="1-getting-started.html#whats-to-come"><i class="fa fa-check"></i><b>1.5.2</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="part"><span><b>I Data Science with tidyverse</b></span></li>
<li class="chapter" data-level="2" data-path="2-viz.html"><a href="2-viz.html"><i class="fa fa-check"></i><b>2</b> Data Visualization</a>
<ul>
<li class="chapter" data-level="" data-path="2-viz.html"><a href="2-viz.html#needed-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="2.1" data-path="2-viz.html"><a href="2-viz.html#grammarofgraphics"><i class="fa fa-check"></i><b>2.1</b> The grammar of graphics</a>
<ul>
<li class="chapter" data-level="2.1.1" data-path="2-viz.html"><a href="2-viz.html#components-of-the-grammar"><i class="fa fa-check"></i><b>2.1.1</b> Components of the grammar</a></li>
<li class="chapter" data-level="2.1.2" data-path="2-viz.html"><a href="2-viz.html#gapminder"><i class="fa fa-check"></i><b>2.1.2</b> Gapminder data</a></li>
<li class="chapter" data-level="2.1.3" data-path="2-viz.html"><a href="2-viz.html#other-components"><i class="fa fa-check"></i><b>2.1.3</b> Other components</a></li>
<li class="chapter" data-level="2.1.4" data-path="2-viz.html"><a href="2-viz.html#ggplot2-package"><i class="fa fa-check"></i><b>2.1.4</b> ggplot2 package</a></li>
</ul></li>
<li class="chapter" data-level="2.2" data-path="2-viz.html"><a href="2-viz.html#FiveNG"><i class="fa fa-check"></i><b>2.2</b> Five named graphs - the 5NG</a></li>
<li class="chapter" data-level="2.3" data-path="2-viz.html"><a href="2-viz.html#scatterplots"><i class="fa fa-check"></i><b>2.3</b> 5NG#1: Scatterplots</a>
<ul>
<li class="chapter" data-level="2.3.1" data-path="2-viz.html"><a href="2-viz.html#geompoint"><i class="fa fa-check"></i><b>2.3.1</b> Scatterplots via <code>geom_point</code></a></li>
<li class="chapter" data-level="2.3.2" data-path="2-viz.html"><a href="2-viz.html#overplotting"><i class="fa fa-check"></i><b>2.3.2</b> Overplotting</a></li>
<li class="chapter" data-level="2.3.3" data-path="2-viz.html"><a href="2-viz.html#summary"><i class="fa fa-check"></i><b>2.3.3</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.4" data-path="2-viz.html"><a href="2-viz.html#linegraphs"><i class="fa fa-check"></i><b>2.4</b> 5NG#2: Linegraphs</a>
<ul>
<li class="chapter" data-level="2.4.1" data-path="2-viz.html"><a href="2-viz.html#geomline"><i class="fa fa-check"></i><b>2.4.1</b> Linegraphs via <code>geom_line</code></a></li>
<li class="chapter" data-level="2.4.2" data-path="2-viz.html"><a href="2-viz.html#summary-1"><i class="fa fa-check"></i><b>2.4.2</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.5" data-path="2-viz.html"><a href="2-viz.html#facets"><i class="fa fa-check"></i><b>2.5</b> Facets</a></li>
<li class="chapter" data-level="2.6" data-path="2-viz.html"><a href="2-viz.html#histograms"><i class="fa fa-check"></i><b>2.6</b> 5NG#3: Histograms</a>
<ul>
<li class="chapter" data-level="2.6.1" data-path="2-viz.html"><a href="2-viz.html#geomhistogram"><i class="fa fa-check"></i><b>2.6.1</b> Histograms via <code>geom_histogram</code></a></li>
<li class="chapter" data-level="2.6.2" data-path="2-viz.html"><a href="2-viz.html#adjustbins"><i class="fa fa-check"></i><b>2.6.2</b> Adjusting the bins</a></li>
<li class="chapter" data-level="2.6.3" data-path="2-viz.html"><a href="2-viz.html#summary-2"><i class="fa fa-check"></i><b>2.6.3</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.7" data-path="2-viz.html"><a href="2-viz.html#boxplots"><i class="fa fa-check"></i><b>2.7</b> 5NG#4: Boxplots</a>
<ul>
<li class="chapter" data-level="2.7.1" data-path="2-viz.html"><a href="2-viz.html#geomboxplot"><i class="fa fa-check"></i><b>2.7.1</b> Boxplots via <code>geom_boxplot</code></a></li>
<li class="chapter" data-level="2.7.2" data-path="2-viz.html"><a href="2-viz.html#summary-3"><i class="fa fa-check"></i><b>2.7.2</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.8" data-path="2-viz.html"><a href="2-viz.html#geombar"><i class="fa fa-check"></i><b>2.8</b> 5NG#5: Barplots</a>
<ul>
<li class="chapter" data-level="2.8.1" data-path="2-viz.html"><a href="2-viz.html#barplots-via-geom_bar-or-geom_col"><i class="fa fa-check"></i><b>2.8.1</b> Barplots via <code>geom_bar</code> or <code>geom_col</code></a></li>
<li class="chapter" data-level="2.8.2" data-path="2-viz.html"><a href="2-viz.html#must-avoid-pie-charts"><i class="fa fa-check"></i><b>2.8.2</b> Must avoid pie charts!</a></li>
<li class="chapter" data-level="2.8.3" data-path="2-viz.html"><a href="2-viz.html#two-categ-barplot"><i class="fa fa-check"></i><b>2.8.3</b> Two categorical variables</a></li>
<li class="chapter" data-level="2.8.4" data-path="2-viz.html"><a href="2-viz.html#summary-4"><i class="fa fa-check"></i><b>2.8.4</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.9" data-path="2-viz.html"><a href="2-viz.html#data-vis-conclusion"><i class="fa fa-check"></i><b>2.9</b> Conclusion</a>
<ul>
<li class="chapter" data-level="2.9.1" data-path="2-viz.html"><a href="2-viz.html#summary-table"><i class="fa fa-check"></i><b>2.9.1</b> Summary table</a></li>
<li class="chapter" data-level="2.9.2" data-path="2-viz.html"><a href="2-viz.html#function-argument-specification"><i class="fa fa-check"></i><b>2.9.2</b> Function argument specification</a></li>
<li class="chapter" data-level="2.9.3" data-path="2-viz.html"><a href="2-viz.html#additional-resources-1"><i class="fa fa-check"></i><b>2.9.3</b> Additional resources</a></li>
<li class="chapter" data-level="2.9.4" data-path="2-viz.html"><a href="2-viz.html#whats-to-come-3"><i class="fa fa-check"></i><b>2.9.4</b> What’s to come</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="3" data-path="3-wrangling.html"><a href="3-wrangling.html"><i class="fa fa-check"></i><b>3</b> Data Wrangling</a>
<ul>
<li class="chapter" data-level="" data-path="3-wrangling.html"><a href="3-wrangling.html#wrangling-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="3.1" data-path="3-wrangling.html"><a href="3-wrangling.html#piping"><i class="fa fa-check"></i><b>3.1</b> The pipe operator: <code>%>%</code></a></li>
<li class="chapter" data-level="3.2" data-path="3-wrangling.html"><a href="3-wrangling.html#filter"><i class="fa fa-check"></i><b>3.2</b> <code>filter</code> rows</a></li>
<li class="chapter" data-level="3.3" data-path="3-wrangling.html"><a href="3-wrangling.html#slice-rows"><i class="fa fa-check"></i><b>3.3</b> <code>slice</code> rows</a></li>
<li class="chapter" data-level="3.4" data-path="3-wrangling.html"><a href="3-wrangling.html#select"><i class="fa fa-check"></i><b>3.4</b> <code>select</code> variables</a>
<ul>
<li class="chapter" data-level="3.4.1" data-path="3-wrangling.html"><a href="3-wrangling.html#rename"><i class="fa fa-check"></i><b>3.4.1</b> <code>rename</code> variables</a></li>
</ul></li>
<li class="chapter" data-level="3.5" data-path="3-wrangling.html"><a href="3-wrangling.html#summarize"><i class="fa fa-check"></i><b>3.5</b> <code>summarize</code> variables</a></li>
<li class="chapter" data-level="3.6" data-path="3-wrangling.html"><a href="3-wrangling.html#groupby"><i class="fa fa-check"></i><b>3.6</b> <code>group_by</code> rows</a>
<ul>
<li class="chapter" data-level="3.6.1" data-path="3-wrangling.html"><a href="3-wrangling.html#grouping-by-more-than-one-variable"><i class="fa fa-check"></i><b>3.6.1</b> Grouping by more than one variable</a></li>
</ul></li>
<li class="chapter" data-level="3.7" data-path="3-wrangling.html"><a href="3-wrangling.html#mutate"><i class="fa fa-check"></i><b>3.7</b> <code>mutate</code> existing variables</a></li>
<li class="chapter" data-level="3.8" data-path="3-wrangling.html"><a href="3-wrangling.html#arrange"><i class="fa fa-check"></i><b>3.8</b> <code>arrange</code> and sort rows</a></li>
<li class="chapter" data-level="3.9" data-path="3-wrangling.html"><a href="3-wrangling.html#wrangling-conclusion"><i class="fa fa-check"></i><b>3.9</b> Conclusion</a>
<ul>
<li class="chapter" data-level="3.9.1" data-path="3-wrangling.html"><a href="3-wrangling.html#summary-table-1"><i class="fa fa-check"></i><b>3.9.1</b> Summary table</a></li>
<li class="chapter" data-level="3.9.2" data-path="3-wrangling.html"><a href="3-wrangling.html#additional-resources-2"><i class="fa fa-check"></i><b>3.9.2</b> Additional resources</a></li>
<li class="chapter" data-level="3.9.3" data-path="3-wrangling.html"><a href="3-wrangling.html#whats-to-come-1"><i class="fa fa-check"></i><b>3.9.3</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="4" data-path="4-tidy.html"><a href="4-tidy.html"><i class="fa fa-check"></i><b>4</b> Data Importing and “Tidy” Data</a>
<ul>
<li class="chapter" data-level="" data-path="4-tidy.html"><a href="4-tidy.html#tidy-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="4.1" data-path="4-tidy.html"><a href="4-tidy.html#csv"><i class="fa fa-check"></i><b>4.1</b> Importing data</a>
<ul>
<li class="chapter" data-level="4.1.1" data-path="4-tidy.html"><a href="4-tidy.html#using-the-console"><i class="fa fa-check"></i><b>4.1.1</b> Using the console</a></li>
<li class="chapter" data-level="4.1.2" data-path="4-tidy.html"><a href="4-tidy.html#using-rstudios-interface"><i class="fa fa-check"></i><b>4.1.2</b> Using RStudio’s interface</a></li>
</ul></li>
<li class="chapter" data-level="4.2" data-path="4-tidy.html"><a href="4-tidy.html#tidy-data-ex"><i class="fa fa-check"></i><b>4.2</b> “Tidy” data</a>
<ul>
<li class="chapter" data-level="4.2.1" data-path="4-tidy.html"><a href="4-tidy.html#tidy-definition"><i class="fa fa-check"></i><b>4.2.1</b> Definition of “tidy” data</a></li>
<li class="chapter" data-level="4.2.2" data-path="4-tidy.html"><a href="4-tidy.html#converting-to-tidy-data"><i class="fa fa-check"></i><b>4.2.2</b> Converting to “tidy” data</a></li>
</ul></li>
<li class="chapter" data-level="4.3" data-path="4-tidy.html"><a href="4-tidy.html#case-study-tidy"><i class="fa fa-check"></i><b>4.3</b> Case study: Weight loss data</a></li>
<li class="chapter" data-level="4.4" data-path="4-tidy.html"><a href="4-tidy.html#tidyverse-package"><i class="fa fa-check"></i><b>4.4</b> <code>tidyverse</code> package</a></li>
<li class="chapter" data-level="4.5" data-path="4-tidy.html"><a href="4-tidy.html#tidy-data-conclusion"><i class="fa fa-check"></i><b>4.5</b> Conclusion</a>
<ul>
<li class="chapter" data-level="4.5.1" data-path="4-tidy.html"><a href="4-tidy.html#additional-resources-3"><i class="fa fa-check"></i><b>4.5.1</b> Additional resources</a></li>
<li class="chapter" data-level="4.5.2" data-path="4-tidy.html"><a href="4-tidy.html#whats-to-come-2"><i class="fa fa-check"></i><b>4.5.2</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="part"><span><b>II Data Modeling with moderndive</b></span></li>
<li class="chapter" data-level="5" data-path="5-regression.html"><a href="5-regression.html"><i class="fa fa-check"></i><b>5</b> Basic Regression</a>
<ul>
<li class="chapter" data-level="" data-path="5-regression.html"><a href="5-regression.html#reg-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="5.1" data-path="5-regression.html"><a href="5-regression.html#model1"><i class="fa fa-check"></i><b>5.1</b> One numerical explanatory variable</a>
<ul>
<li class="chapter" data-level="5.1.1" data-path="5-regression.html"><a href="5-regression.html#model1EDA"><i class="fa fa-check"></i><b>5.1.1</b> Exploratory data analysis</a></li>
<li class="chapter" data-level="5.1.2" data-path="5-regression.html"><a href="5-regression.html#model1table"><i class="fa fa-check"></i><b>5.1.2</b> Simple linear regression</a></li>
<li class="chapter" data-level="5.1.3" data-path="5-regression.html"><a href="5-regression.html#model1points"><i class="fa fa-check"></i><b>5.1.3</b> Observed/fitted values and residuals</a></li>
</ul></li>
<li class="chapter" data-level="5.2" data-path="5-regression.html"><a href="5-regression.html#model2"><i class="fa fa-check"></i><b>5.2</b> One categorical explanatory variable</a>
<ul>
<li class="chapter" data-level="5.2.1" data-path="5-regression.html"><a href="5-regression.html#model2EDA"><i class="fa fa-check"></i><b>5.2.1</b> Exploratory data analysis</a></li>
<li class="chapter" data-level="5.2.2" data-path="5-regression.html"><a href="5-regression.html#model2table"><i class="fa fa-check"></i><b>5.2.2</b> Linear regression</a></li>
<li class="chapter" data-level="5.2.3" data-path="5-regression.html"><a href="5-regression.html#model2points"><i class="fa fa-check"></i><b>5.2.3</b> Observed/fitted values and residuals</a></li>
</ul></li>
<li class="chapter" data-level="5.3" data-path="5-regression.html"><a href="5-regression.html#reg-related-topics"><i class="fa fa-check"></i><b>5.3</b> Related topics</a>
<ul>
<li class="chapter" data-level="5.3.1" data-path="5-regression.html"><a href="5-regression.html#correlation-is-not-causation"><i class="fa fa-check"></i><b>5.3.1</b> Correlation is not necessarily causation</a></li>
<li class="chapter" data-level="5.3.2" data-path="5-regression.html"><a href="5-regression.html#leastsquares"><i class="fa fa-check"></i><b>5.3.2</b> Best-fitting line</a></li>
<li class="chapter" data-level="5.3.3" data-path="5-regression.html"><a href="5-regression.html#underthehood"><i class="fa fa-check"></i><b>5.3.3</b> <code>get_regression_x()</code> functions</a></li>
</ul></li>
<li class="chapter" data-level="5.4" data-path="5-regression.html"><a href="5-regression.html#reg-conclusion"><i class="fa fa-check"></i><b>5.4</b> Conclusion</a>
<ul>
<li class="chapter" data-level="5.4.1" data-path="5-regression.html"><a href="5-regression.html#additional-resources-basic-regression"><i class="fa fa-check"></i><b>5.4.1</b> Additional resources</a></li>
<li class="chapter" data-level="5.4.2" data-path="5-regression.html"><a href="5-regression.html#whats-to-come-4"><i class="fa fa-check"></i><b>5.4.2</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="6" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html"><i class="fa fa-check"></i><b>6</b> Multiple Regression</a>
<ul>
<li class="chapter" data-level="" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#mult-reg-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="6.1" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model4"><i class="fa fa-check"></i><b>6.1</b> One numerical and one categorical explanatory variable</a>
<ul>
<li class="chapter" data-level="6.1.1" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model4EDA"><i class="fa fa-check"></i><b>6.1.1</b> Exploratory data analysis</a></li>
<li class="chapter" data-level="6.1.2" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model4interactiontable"><i class="fa fa-check"></i><b>6.1.2</b> Interaction model</a></li>
<li class="chapter" data-level="6.1.3" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model4table"><i class="fa fa-check"></i><b>6.1.3</b> Parallel slopes model</a></li>
<li class="chapter" data-level="6.1.4" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model4points"><i class="fa fa-check"></i><b>6.1.4</b> Observed/fitted values and residuals</a></li>
</ul></li>
<li class="chapter" data-level="6.2" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model3"><i class="fa fa-check"></i><b>6.2</b> Two categorical explanatory variables</a>
<ul>
<li class="chapter" data-level="6.2.1" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model3EDA"><i class="fa fa-check"></i><b>6.2.1</b> Exploratory data analysis</a></li>
<li class="chapter" data-level="6.2.2" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model3table"><i class="fa fa-check"></i><b>6.2.2</b> Regression lines</a></li>
<li class="chapter" data-level="6.2.3" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model3points"><i class="fa fa-check"></i><b>6.2.3</b> Observed/fitted values and residuals</a></li>
</ul></li>
<li class="chapter" data-level="6.3" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#mult-reg-related-topics"><i class="fa fa-check"></i><b>6.3</b> Related topics</a>
<ul>
<li class="chapter" data-level="6.3.1" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#model-selection"><i class="fa fa-check"></i><b>6.3.1</b> Model selection using visualizations</a></li>
<li class="chapter" data-level="6.3.2" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#rsquared"><i class="fa fa-check"></i><b>6.3.2</b> Model selection using R-squared</a></li>
</ul></li>
<li class="chapter" data-level="6.4" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#mult-reg-conclusion"><i class="fa fa-check"></i><b>6.4</b> Conclusion</a>
<ul>
<li class="chapter" data-level="6.4.1" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#additional-resources-4"><i class="fa fa-check"></i><b>6.4.1</b> Additional resources</a></li>
<li class="chapter" data-level="6.4.2" data-path="6-multiple-regression.html"><a href="6-multiple-regression.html#whats-to-come-5"><i class="fa fa-check"></i><b>6.4.2</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="part"><span><b>III Statistical Inference with infer</b></span></li>
<li class="chapter" data-level="7" data-path="7-sampling.html"><a href="7-sampling.html"><i class="fa fa-check"></i><b>7</b> Sampling</a>
<ul>
<li class="chapter" data-level="" data-path="7-sampling.html"><a href="7-sampling.html#sampling-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="7.1" data-path="7-sampling.html"><a href="7-sampling.html#sampling-activity"><i class="fa fa-check"></i><b>7.1</b> Sampling bowl activity</a>
<ul>
<li class="chapter" data-level="7.1.1" data-path="7-sampling.html"><a href="7-sampling.html#what-proportion-of-this-bowls-balls-are-red"><i class="fa fa-check"></i><b>7.1.1</b> What proportion of this bowl’s balls are red?</a></li>
<li class="chapter" data-level="7.1.2" data-path="7-sampling.html"><a href="7-sampling.html#using-the-shovel-once"><i class="fa fa-check"></i><b>7.1.2</b> Using the shovel once</a></li>
<li class="chapter" data-level="7.1.3" data-path="7-sampling.html"><a href="7-sampling.html#student-shovels"><i class="fa fa-check"></i><b>7.1.3</b> Using the shovel 33 times</a></li>
<li class="chapter" data-level="7.1.4" data-path="7-sampling.html"><a href="7-sampling.html#sampling-what-did-we-just-do"><i class="fa fa-check"></i><b>7.1.4</b> What did we just do?</a></li>
</ul></li>
<li class="chapter" data-level="7.2" data-path="7-sampling.html"><a href="7-sampling.html#sampling-simulation"><i class="fa fa-check"></i><b>7.2</b> Virtual sampling</a>
<ul>
<li class="chapter" data-level="7.2.1" data-path="7-sampling.html"><a href="7-sampling.html#using-the-virtual-shovel-once"><i class="fa fa-check"></i><b>7.2.1</b> Using the virtual shovel once</a></li>
</ul></li>
<li class="chapter" data-level="7.3" data-path="7-sampling.html"><a href="7-sampling.html#sampling-framework"><i class="fa fa-check"></i><b>7.3</b> Sampling framework</a>
<ul>
<li class="chapter" data-level="7.3.1" data-path="7-sampling.html"><a href="7-sampling.html#terminology-and-notation"><i class="fa fa-check"></i><b>7.3.1</b> Terminology and notation</a></li>
<li class="chapter" data-level="7.3.2" data-path="7-sampling.html"><a href="7-sampling.html#sampling-definitions"><i class="fa fa-check"></i><b>7.3.2</b> Statistical definitions</a></li>
<li class="chapter" data-level="7.3.3" data-path="7-sampling.html"><a href="7-sampling.html#moral-of-the-story"><i class="fa fa-check"></i><b>7.3.3</b> The moral of the story</a></li>
</ul></li>
<li class="chapter" data-level="7.4" data-path="7-sampling.html"><a href="7-sampling.html#sampling-case-study"><i class="fa fa-check"></i><b>7.4</b> Case study: Genetic crosses</a></li>
<li class="chapter" data-level="7.5" data-path="7-sampling.html"><a href="7-sampling.html#sampling-conclusion-central-limit-theorem"><i class="fa fa-check"></i><b>7.5</b> Central Limit Theorem</a></li>
<li class="chapter" data-level="7.6" data-path="7-sampling.html"><a href="7-sampling.html#sampling-conclusion"><i class="fa fa-check"></i><b>7.6</b> Conclusion</a>
<ul>
<li class="chapter" data-level="7.6.1" data-path="7-sampling.html"><a href="7-sampling.html#sampling-conclusion-table"><i class="fa fa-check"></i><b>7.6.1</b> Sampling scenarios</a></li>
<li class="chapter" data-level="7.6.2" data-path="7-sampling.html"><a href="7-sampling.html#additional-resources-5"><i class="fa fa-check"></i><b>7.6.2</b> Additional resources</a></li>
<li class="chapter" data-level="7.6.3" data-path="7-sampling.html"><a href="7-sampling.html#whats-to-come-6"><i class="fa fa-check"></i><b>7.6.3</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="8" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html"><i class="fa fa-check"></i><b>8</b> Bootstrapping and Confidence Intervals</a>
<ul>
<li class="chapter" data-level="" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#CI-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="8.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#resampling-tactile"><i class="fa fa-check"></i><b>8.1</b> Pennies activity</a>
<ul>
<li class="chapter" data-level="8.1.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#what-is-the-average-year-on-us-pennies-in-2019"><i class="fa fa-check"></i><b>8.1.1</b> What is the average year on US pennies in 2019?</a></li>
<li class="chapter" data-level="8.1.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#resampling-once"><i class="fa fa-check"></i><b>8.1.2</b> Resampling once</a></li>
<li class="chapter" data-level="8.1.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#student-resamples"><i class="fa fa-check"></i><b>8.1.3</b> Resampling 35 times</a></li>
<li class="chapter" data-level="8.1.4" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ci-what-did-we-just-do"><i class="fa fa-check"></i><b>8.1.4</b> What did we just do?</a></li>
</ul></li>
<li class="chapter" data-level="8.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#resampling-simulation"><i class="fa fa-check"></i><b>8.2</b> Computer simulation of resampling</a>
<ul>
<li class="chapter" data-level="8.2.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#virtually-resampling-once"><i class="fa fa-check"></i><b>8.2.1</b> Virtually resampling once</a></li>
<li class="chapter" data-level="8.2.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#bootstrap-35-replicates"><i class="fa fa-check"></i><b>8.2.2</b> Virtually resampling 35 times</a></li>
<li class="chapter" data-level="8.2.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#bootstrap-1000-replicates"><i class="fa fa-check"></i><b>8.2.3</b> Virtually resampling 1000 times</a></li>
</ul></li>
<li class="chapter" data-level="8.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ci-build-up"><i class="fa fa-check"></i><b>8.3</b> Understanding confidence intervals</a>
<ul>
<li class="chapter" data-level="8.3.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#percentile-method"><i class="fa fa-check"></i><b>8.3.1</b> Percentile method</a></li>
<li class="chapter" data-level="8.3.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#se-method"><i class="fa fa-check"></i><b>8.3.2</b> Standard error method</a></li>
</ul></li>
<li class="chapter" data-level="8.4" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#bootstrap-process"><i class="fa fa-check"></i><b>8.4</b> Constructing confidence intervals</a>
<ul>
<li class="chapter" data-level="8.4.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#original-workflow"><i class="fa fa-check"></i><b>8.4.1</b> Original workflow</a></li>
<li class="chapter" data-level="8.4.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#infer-workflow"><i class="fa fa-check"></i><b>8.4.2</b> <code>infer</code> package workflow</a></li>
<li class="chapter" data-level="8.4.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#percentile-method-infer"><i class="fa fa-check"></i><b>8.4.3</b> Percentile method with <code>infer</code></a></li>
<li class="chapter" data-level="8.4.4" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#infer-se"><i class="fa fa-check"></i><b>8.4.4</b> Standard error method with <code>infer</code></a></li>
</ul></li>
<li class="chapter" data-level="8.5" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#one-prop-ci"><i class="fa fa-check"></i><b>8.5</b> Interpreting confidence intervals</a>
<ul>
<li class="chapter" data-level="8.5.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ilyas-yohan"><i class="fa fa-check"></i><b>8.5.1</b> Did the net capture the fish?</a></li>
<li class="chapter" data-level="8.5.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#shorthand"><i class="fa fa-check"></i><b>8.5.2</b> Precise and shorthand interpretation</a></li>
<li class="chapter" data-level="8.5.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ci-width"><i class="fa fa-check"></i><b>8.5.3</b> Width of confidence intervals</a></li>
</ul></li>
<li class="chapter" data-level="8.6" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#case-study-two-prop-ci"><i class="fa fa-check"></i><b>8.6</b> Case study: Is yawning contagious?</a>
<ul>
<li class="chapter" data-level="8.6.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#mythbusters-study-data"><i class="fa fa-check"></i><b>8.6.1</b> <em>Mythbusters</em> study data</a></li>
<li class="chapter" data-level="8.6.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#sampling-scenario"><i class="fa fa-check"></i><b>8.6.2</b> Sampling scenario</a></li>
<li class="chapter" data-level="8.6.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ci-build"><i class="fa fa-check"></i><b>8.6.3</b> Constructing the confidence interval</a></li>
<li class="chapter" data-level="8.6.4" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#interpreting-the-confidence-interval"><i class="fa fa-check"></i><b>8.6.4</b> Interpreting the confidence interval</a></li>
</ul></li>
<li class="chapter" data-level="8.7" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#ci-conclusion"><i class="fa fa-check"></i><b>8.7</b> Conclusion</a>
<ul>
<li class="chapter" data-level="8.7.1" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#bootstrap-vs-sampling"><i class="fa fa-check"></i><b>8.7.1</b> Comparing bootstrap and sampling distributions</a></li>
<li class="chapter" data-level="8.7.2" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#theory-ci"><i class="fa fa-check"></i><b>8.7.2</b> Theory-based confidence intervals</a></li>
<li class="chapter" data-level="8.7.3" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#additional-resources-6"><i class="fa fa-check"></i><b>8.7.3</b> Additional resources</a></li>
<li class="chapter" data-level="8.7.4" data-path="8-confidence-intervals.html"><a href="8-confidence-intervals.html#whats-to-come-7"><i class="fa fa-check"></i><b>8.7.4</b> What’s to come?</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="9" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html"><i class="fa fa-check"></i><b>9</b> Hypothesis Testing</a>
<ul>
<li class="chapter" data-level="" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#nhst-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="9.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#ht-activity"><i class="fa fa-check"></i><b>9.1</b> Clutch size and malaria resistance</a>
<ul>
<li class="chapter" data-level="9.1.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#is-there-a-tradeoff-between-reproduction-and-immune-defense"><i class="fa fa-check"></i><b>9.1.1</b> Is there a tradeoff between reproduction and immune defense?</a></li>
<li class="chapter" data-level="9.1.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#shuffling-once"><i class="fa fa-check"></i><b>9.1.2</b> Shuffling once</a></li>
<li class="chapter" data-level="9.1.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#shuffling-99-more-times"><i class="fa fa-check"></i><b>9.1.3</b> Shuffling 99 more times</a></li>
<li class="chapter" data-level="9.1.4" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#ht-what-did-we-just-do"><i class="fa fa-check"></i><b>9.1.4</b> What did we just do?</a></li>
</ul></li>
<li class="chapter" data-level="9.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#understanding-ht"><i class="fa fa-check"></i><b>9.2</b> Understanding hypothesis tests</a></li>
<li class="chapter" data-level="9.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#ht-infer"><i class="fa fa-check"></i><b>9.3</b> Conducting hypothesis tests</a>
<ul>
<li class="chapter" data-level="9.3.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#infer-workflow-ht"><i class="fa fa-check"></i><b>9.3.1</b> <code>infer</code> package workflow</a></li>
<li class="chapter" data-level="9.3.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#comparing-infer-workflows"><i class="fa fa-check"></i><b>9.3.2</b> Comparison with confidence intervals</a></li>
<li class="chapter" data-level="9.3.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#only-one-test"><i class="fa fa-check"></i><b>9.3.3</b> “There is only one test”</a></li>
</ul></li>
<li class="chapter" data-level="9.4" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#ht-interpretation"><i class="fa fa-check"></i><b>9.4</b> Interpreting hypothesis tests</a>
<ul>
<li class="chapter" data-level="9.4.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#trial"><i class="fa fa-check"></i><b>9.4.1</b> Two possible outcomes</a></li>
<li class="chapter" data-level="9.4.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#types-of-errors"><i class="fa fa-check"></i><b>9.4.2</b> Types of errors</a></li>
<li class="chapter" data-level="9.4.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#choosing-alpha"><i class="fa fa-check"></i><b>9.4.3</b> How do we choose alpha?</a></li>
</ul></li>
<li class="chapter" data-level="9.5" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#ht-case-study"><i class="fa fa-check"></i><b>9.5</b> Case study: Do living lizards have longer horns than dead lizards?</a>
<ul>
<li class="chapter" data-level="9.5.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#imdb-data"><i class="fa fa-check"></i><b>9.5.1</b> Horned lizards dataset</a></li>
<li class="chapter" data-level="9.5.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#sampling-scenario-1"><i class="fa fa-check"></i><b>9.5.2</b> Sampling scenario</a></li>
<li class="chapter" data-level="9.5.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#conducting-the-hypothesis-test"><i class="fa fa-check"></i><b>9.5.3</b> Conducting the hypothesis test</a></li>
</ul></li>
<li class="chapter" data-level="9.6" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#nhst-conclusion"><i class="fa fa-check"></i><b>9.6</b> Conclusion</a>
<ul>
<li class="chapter" data-level="9.6.1" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#theory-hypo"><i class="fa fa-check"></i><b>9.6.1</b> Theory-based hypothesis tests</a></li>
<li class="chapter" data-level="9.6.2" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#problems-with-p-values"><i class="fa fa-check"></i><b>9.6.2</b> Problems with p-values</a></li>
<li class="chapter" data-level="9.6.3" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#additional-resources-7"><i class="fa fa-check"></i><b>9.6.3</b> Additional resources</a></li>
<li class="chapter" data-level="9.6.4" data-path="9-hypothesis-testing.html"><a href="9-hypothesis-testing.html#whats-to-come-8"><i class="fa fa-check"></i><b>9.6.4</b> What’s to come</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="10" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html"><i class="fa fa-check"></i><b>10</b> Inference for Regression</a>
<ul>
<li class="chapter" data-level="" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#inf-packages"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="10.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-refresher"><i class="fa fa-check"></i><b>10.1</b> Regression refresher</a>
<ul>
<li class="chapter" data-level="10.1.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#lion-age-and-nose-coloration"><i class="fa fa-check"></i><b>10.1.1</b> Lion age and nose coloration</a></li>
<li class="chapter" data-level="10.1.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#sampling-scenario-2"><i class="fa fa-check"></i><b>10.1.2</b> Sampling scenario</a></li>
</ul></li>
<li class="chapter" data-level="10.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-interp"><i class="fa fa-check"></i><b>10.2</b> Interpreting regression tables</a>
<ul>
<li class="chapter" data-level="10.2.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-se"><i class="fa fa-check"></i><b>10.2.1</b> Standard error</a></li>
<li class="chapter" data-level="10.2.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-test-statistic"><i class="fa fa-check"></i><b>10.2.2</b> Test statistic</a></li>
<li class="chapter" data-level="10.2.3" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#p-value"><i class="fa fa-check"></i><b>10.2.3</b> p-value</a></li>
<li class="chapter" data-level="10.2.4" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#confidence-interval"><i class="fa fa-check"></i><b>10.2.4</b> Confidence interval</a></li>
<li class="chapter" data-level="10.2.5" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-table-computation"><i class="fa fa-check"></i><b>10.2.5</b> How does R compute the table?</a></li>
</ul></li>
<li class="chapter" data-level="10.3" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#regression-conditions"><i class="fa fa-check"></i><b>10.3</b> Conditions for inference for regression</a>
<ul>
<li class="chapter" data-level="10.3.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#residuals-refresher"><i class="fa fa-check"></i><b>10.3.1</b> Residuals refresher</a></li>
<li class="chapter" data-level="10.3.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#linearity-of-relationship"><i class="fa fa-check"></i><b>10.3.2</b> Linearity of relationship</a></li>
<li class="chapter" data-level="10.3.3" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#independence-of-residuals"><i class="fa fa-check"></i><b>10.3.3</b> Independence of residuals</a></li>
<li class="chapter" data-level="10.3.4" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#normality-of-residuals"><i class="fa fa-check"></i><b>10.3.4</b> Normality of residuals</a></li>
<li class="chapter" data-level="10.3.5" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#equality-of-variance"><i class="fa fa-check"></i><b>10.3.5</b> Equality of variance</a></li>
<li class="chapter" data-level="10.3.6" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#what-is-the-conclusion"><i class="fa fa-check"></i><b>10.3.6</b> What’s the conclusion?</a></li>
</ul></li>
<li class="chapter" data-level="10.4" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#infer-regression"><i class="fa fa-check"></i><b>10.4</b> Simulation-based inference for regression</a>
<ul>
<li class="chapter" data-level="10.4.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#confidence-interval-for-slope"><i class="fa fa-check"></i><b>10.4.1</b> Confidence interval for slope</a></li>
<li class="chapter" data-level="10.4.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#hypothesis-test-for-slope"><i class="fa fa-check"></i><b>10.4.2</b> Hypothesis test for slope</a></li>
</ul></li>
<li class="chapter" data-level="10.5" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#inference-conclusion"><i class="fa fa-check"></i><b>10.5</b> Conclusion</a>
<ul>
<li class="chapter" data-level="10.5.1" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#theory-regression"><i class="fa fa-check"></i><b>10.5.1</b> Theory-based inference for regression</a></li>
<li class="chapter" data-level="10.5.2" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#summary-of-statistical-inference"><i class="fa fa-check"></i><b>10.5.2</b> Summary of statistical inference</a></li>
<li class="chapter" data-level="10.5.3" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#additional-resources-8"><i class="fa fa-check"></i><b>10.5.3</b> Additional resources</a></li>
<li class="chapter" data-level="10.5.4" data-path="10-inference-for-regression.html"><a href="10-inference-for-regression.html#whats-to-come-9"><i class="fa fa-check"></i><b>10.5.4</b> What’s to come</a></li>
</ul></li>
</ul></li>
<li class="part"><span><b>IV Conclusion</b></span></li>
<li class="chapter" data-level="11" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html"><i class="fa fa-check"></i><b>11</b> Tell Your Story with Data</a>
<ul>
<li class="chapter" data-level="11.1" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#review"><i class="fa fa-check"></i><b>11.1</b> Review</a>
<ul>
<li class="chapter" data-level="" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#story-packages"><i class="fa fa-check"></i>Needed packages</a></li>
</ul></li>
<li class="chapter" data-level="11.2" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#seattle-house-prices"><i class="fa fa-check"></i><b>11.2</b> Case study: Seattle house prices</a>
<ul>
<li class="chapter" data-level="11.2.1" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#house-prices-EDA-I"><i class="fa fa-check"></i><b>11.2.1</b> Exploratory data analysis: Part I</a></li>
<li class="chapter" data-level="11.2.2" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#house-prices-EDA-II"><i class="fa fa-check"></i><b>11.2.2</b> Exploratory data analysis: Part II</a></li>
<li class="chapter" data-level="11.2.3" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#house-prices-regression"><i class="fa fa-check"></i><b>11.2.3</b> Regression modeling</a></li>
<li class="chapter" data-level="11.2.4" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#house-prices-making-predictions"><i class="fa fa-check"></i><b>11.2.4</b> Making predictions</a></li>
</ul></li>
<li class="chapter" data-level="11.3" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#data-journalism"><i class="fa fa-check"></i><b>11.3</b> Case study: Effective data storytelling</a>
<ul>
<li class="chapter" data-level="11.3.1" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#bechdel-test-for-hollywood-gender-representation"><i class="fa fa-check"></i><b>11.3.1</b> Bechdel test for Hollywood gender representation</a></li>
<li class="chapter" data-level="11.3.2" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#us-births-in-1999"><i class="fa fa-check"></i><b>11.3.2</b> US Births in 1999</a></li>
<li class="chapter" data-level="11.3.3" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#scripts-of-r-code"><i class="fa fa-check"></i><b>11.3.3</b> Scripts of R code</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="11-thinking-with-data.html"><a href="11-thinking-with-data.html#concluding-remarks"><i class="fa fa-check"></i>Concluding remarks</a></li>
</ul></li>
<li class="appendix"><span><b>Appendix</b></span></li>
<li class="chapter" data-level="A" data-path="A-appendixA.html"><a href="A-appendixA.html"><i class="fa fa-check"></i><b>A</b> Statistical Background</a>
<ul>
<li class="chapter" data-level="A.1" data-path="A-appendixA.html"><a href="A-appendixA.html#appendix-stat-terms"><i class="fa fa-check"></i><b>A.1</b> Basic statistical terms</a>
<ul>
<li class="chapter" data-level="A.1.1" data-path="A-appendixA.html"><a href="A-appendixA.html#mean"><i class="fa fa-check"></i><b>A.1.1</b> Mean</a></li>
<li class="chapter" data-level="A.1.2" data-path="A-appendixA.html"><a href="A-appendixA.html#median"><i class="fa fa-check"></i><b>A.1.2</b> Median</a></li>
<li class="chapter" data-level="A.1.3" data-path="A-appendixA.html"><a href="A-appendixA.html#appendix-sd-variance"><i class="fa fa-check"></i><b>A.1.3</b> Standard deviation and variance</a></li>
<li class="chapter" data-level="A.1.4" data-path="A-appendixA.html"><a href="A-appendixA.html#five-number-summary"><i class="fa fa-check"></i><b>A.1.4</b> Five-number summary</a></li>
<li class="chapter" data-level="A.1.5" data-path="A-appendixA.html"><a href="A-appendixA.html#distribution"><i class="fa fa-check"></i><b>A.1.5</b> Distribution</a></li>
<li class="chapter" data-level="A.1.6" data-path="A-appendixA.html"><a href="A-appendixA.html#outliers"><i class="fa fa-check"></i><b>A.1.6</b> Outliers</a></li>
</ul></li>
<li class="chapter" data-level="A.2" data-path="A-appendixA.html"><a href="A-appendixA.html#appendix-normal-curve"><i class="fa fa-check"></i><b>A.2</b> Normal distribution</a></li>
<li class="chapter" data-level="A.3" data-path="A-appendixA.html"><a href="A-appendixA.html#appendix-log10-transformations"><i class="fa fa-check"></i><b>A.3</b> log10 transformations</a></li>
</ul></li>
<li class="chapter" data-level="B" data-path="B-appendixB.html"><a href="B-appendixB.html"><i class="fa fa-check"></i><b>B</b> Inference Examples</a>
<ul>
<li class="chapter" data-level="" data-path="B-appendixB.html"><a href="B-appendixB.html#needed-packages-1"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="B.1" data-path="B-appendixB.html"><a href="B-appendixB.html#inference-mind-map"><i class="fa fa-check"></i><b>B.1</b> Inference mind map</a></li>
<li class="chapter" data-level="B.2" data-path="B-appendixB.html"><a href="B-appendixB.html#one-mean"><i class="fa fa-check"></i><b>B.2</b> One mean</a>
<ul>
<li class="chapter" data-level="B.2.1" data-path="B-appendixB.html"><a href="B-appendixB.html#problem-statement"><i class="fa fa-check"></i><b>B.2.1</b> Problem statement</a></li>
<li class="chapter" data-level="B.2.2" data-path="B-appendixB.html"><a href="B-appendixB.html#competing-hypotheses"><i class="fa fa-check"></i><b>B.2.2</b> Competing hypotheses</a></li>
<li class="chapter" data-level="B.2.3" data-path="B-appendixB.html"><a href="B-appendixB.html#exploring-the-sample-data"><i class="fa fa-check"></i><b>B.2.3</b> Exploring the sample data</a></li>
<li class="chapter" data-level="B.2.4" data-path="B-appendixB.html"><a href="B-appendixB.html#non-traditional-methods"><i class="fa fa-check"></i><b>B.2.4</b> Non-traditional methods</a></li>
<li class="chapter" data-level="B.2.5" data-path="B-appendixB.html"><a href="B-appendixB.html#traditional-methods"><i class="fa fa-check"></i><b>B.2.5</b> Traditional methods</a></li>
<li class="chapter" data-level="B.2.6" data-path="B-appendixB.html"><a href="B-appendixB.html#comparing-results"><i class="fa fa-check"></i><b>B.2.6</b> Comparing results</a></li>
</ul></li>
<li class="chapter" data-level="B.3" data-path="B-appendixB.html"><a href="B-appendixB.html#one-proportion"><i class="fa fa-check"></i><b>B.3</b> One proportion</a>
<ul>
<li class="chapter" data-level="B.3.1" data-path="B-appendixB.html"><a href="B-appendixB.html#problem-statement-1"><i class="fa fa-check"></i><b>B.3.1</b> Problem statement</a></li>
<li class="chapter" data-level="B.3.2" data-path="B-appendixB.html"><a href="B-appendixB.html#competing-hypotheses-1"><i class="fa fa-check"></i><b>B.3.2</b> Competing hypotheses</a></li>
<li class="chapter" data-level="B.3.3" data-path="B-appendixB.html"><a href="B-appendixB.html#exploring-the-sample-data-1"><i class="fa fa-check"></i><b>B.3.3</b> Exploring the sample data</a></li>
<li class="chapter" data-level="B.3.4" data-path="B-appendixB.html"><a href="B-appendixB.html#non-traditional-methods-1"><i class="fa fa-check"></i><b>B.3.4</b> Non-traditional methods</a></li>
<li class="chapter" data-level="B.3.5" data-path="B-appendixB.html"><a href="B-appendixB.html#traditional-methods-1"><i class="fa fa-check"></i><b>B.3.5</b> Traditional methods</a></li>
<li class="chapter" data-level="B.3.6" data-path="B-appendixB.html"><a href="B-appendixB.html#comparing-results-1"><i class="fa fa-check"></i><b>B.3.6</b> Comparing results</a></li>
</ul></li>
<li class="chapter" data-level="B.4" data-path="B-appendixB.html"><a href="B-appendixB.html#two-proportions"><i class="fa fa-check"></i><b>B.4</b> Two proportions</a>
<ul>
<li class="chapter" data-level="B.4.1" data-path="B-appendixB.html"><a href="B-appendixB.html#problem-statement-2"><i class="fa fa-check"></i><b>B.4.1</b> Problem statement</a></li>
<li class="chapter" data-level="B.4.2" data-path="B-appendixB.html"><a href="B-appendixB.html#competing-hypotheses-2"><i class="fa fa-check"></i><b>B.4.2</b> Competing hypotheses</a></li>
<li class="chapter" data-level="B.4.3" data-path="B-appendixB.html"><a href="B-appendixB.html#exploring-the-sample-data-2"><i class="fa fa-check"></i><b>B.4.3</b> Exploring the sample data</a></li>
<li class="chapter" data-level="B.4.4" data-path="B-appendixB.html"><a href="B-appendixB.html#non-traditional-methods-2"><i class="fa fa-check"></i><b>B.4.4</b> Non-traditional methods</a></li>
<li class="chapter" data-level="B.4.5" data-path="B-appendixB.html"><a href="B-appendixB.html#traditional-methods-2"><i class="fa fa-check"></i><b>B.4.5</b> Traditional methods</a></li>
<li class="chapter" data-level="B.4.6" data-path="B-appendixB.html"><a href="B-appendixB.html#test-statistic-2"><i class="fa fa-check"></i><b>B.4.6</b> Test statistic</a></li>
<li class="chapter" data-level="B.4.7" data-path="B-appendixB.html"><a href="B-appendixB.html#state-conclusion-2"><i class="fa fa-check"></i><b>B.4.7</b> State conclusion</a></li>
<li class="chapter" data-level="B.4.8" data-path="B-appendixB.html"><a href="B-appendixB.html#comparing-results-2"><i class="fa fa-check"></i><b>B.4.8</b> Comparing results</a></li>
</ul></li>
<li class="chapter" data-level="B.5" data-path="B-appendixB.html"><a href="B-appendixB.html#two-means-independent-samples"><i class="fa fa-check"></i><b>B.5</b> Two means (independent samples)</a>
<ul>
<li class="chapter" data-level="B.5.1" data-path="B-appendixB.html"><a href="B-appendixB.html#problem-statement-3"><i class="fa fa-check"></i><b>B.5.1</b> Problem statement</a></li>
<li class="chapter" data-level="B.5.2" data-path="B-appendixB.html"><a href="B-appendixB.html#competing-hypotheses-3"><i class="fa fa-check"></i><b>B.5.2</b> Competing hypotheses</a></li>
<li class="chapter" data-level="B.5.3" data-path="B-appendixB.html"><a href="B-appendixB.html#exploring-the-sample-data-3"><i class="fa fa-check"></i><b>B.5.3</b> Exploring the sample data</a></li>
<li class="chapter" data-level="B.5.4" data-path="B-appendixB.html"><a href="B-appendixB.html#non-traditional-methods-3"><i class="fa fa-check"></i><b>B.5.4</b> Non-traditional methods</a></li>
<li class="chapter" data-level="B.5.5" data-path="B-appendixB.html"><a href="B-appendixB.html#traditional-methods-3"><i class="fa fa-check"></i><b>B.5.5</b> Traditional methods</a></li>
<li class="chapter" data-level="B.5.6" data-path="B-appendixB.html"><a href="B-appendixB.html#test-statistic-3"><i class="fa fa-check"></i><b>B.5.6</b> Test statistic</a></li>
<li class="chapter" data-level="B.5.7" data-path="B-appendixB.html"><a href="B-appendixB.html#compute-p-value-1"><i class="fa fa-check"></i><b>B.5.7</b> Compute <span class="math inline">\(p\)</span>-value</a></li>
<li class="chapter" data-level="B.5.8" data-path="B-appendixB.html"><a href="B-appendixB.html#state-conclusion-3"><i class="fa fa-check"></i><b>B.5.8</b> State conclusion</a></li>
<li class="chapter" data-level="B.5.9" data-path="B-appendixB.html"><a href="B-appendixB.html#comparing-results-3"><i class="fa fa-check"></i><b>B.5.9</b> Comparing results</a></li>
</ul></li>
<li class="chapter" data-level="B.6" data-path="B-appendixB.html"><a href="B-appendixB.html#two-means-paired-samples"><i class="fa fa-check"></i><b>B.6</b> Two means (paired samples)</a>
<ul>
<li class="chapter" data-level="" data-path="B-appendixB.html"><a href="B-appendixB.html#problem-statement-4"><i class="fa fa-check"></i>Problem statement</a></li>
<li class="chapter" data-level="B.6.1" data-path="B-appendixB.html"><a href="B-appendixB.html#competing-hypotheses-4"><i class="fa fa-check"></i><b>B.6.1</b> Competing hypotheses</a></li>
<li class="chapter" data-level="B.6.2" data-path="B-appendixB.html"><a href="B-appendixB.html#exploring-the-sample-data-4"><i class="fa fa-check"></i><b>B.6.2</b> Exploring the sample data</a></li>
<li class="chapter" data-level="B.6.3" data-path="B-appendixB.html"><a href="B-appendixB.html#non-traditional-methods-4"><i class="fa fa-check"></i><b>B.6.3</b> Non-traditional methods</a></li>
<li class="chapter" data-level="B.6.4" data-path="B-appendixB.html"><a href="B-appendixB.html#traditional-methods-4"><i class="fa fa-check"></i><b>B.6.4</b> Traditional methods</a></li>
<li class="chapter" data-level="B.6.5" data-path="B-appendixB.html"><a href="B-appendixB.html#comparing-results-4"><i class="fa fa-check"></i><b>B.6.5</b> Comparing results</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="C" data-path="C-appendixC.html"><a href="C-appendixC.html"><i class="fa fa-check"></i><b>C</b> Tips and Tricks</a>
<ul>
<li class="chapter" data-level="" data-path="C-appendixC.html"><a href="C-appendixC.html#needed-packages-2"><i class="fa fa-check"></i>Needed packages</a></li>
<li class="chapter" data-level="C.1" data-path="C-appendixC.html"><a href="C-appendixC.html#data-wrangling"><i class="fa fa-check"></i><b>C.1</b> Data wrangling</a>
<ul>
<li class="chapter" data-level="C.1.1" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-missing-values"><i class="fa fa-check"></i><b>C.1.1</b> Dealing with missing values</a></li>
<li class="chapter" data-level="C.1.2" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-reordering-bars"><i class="fa fa-check"></i><b>C.1.2</b> Reordering bars in a barplot</a></li>
<li class="chapter" data-level="C.1.3" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-money-on-axis"><i class="fa fa-check"></i><b>C.1.3</b> Showing money on an axis</a></li>
<li class="chapter" data-level="C.1.4" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-changing-values"><i class="fa fa-check"></i><b>C.1.4</b> Changing values inside cells</a></li>
<li class="chapter" data-level="C.1.5" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-convert-numerical-categorical"><i class="fa fa-check"></i><b>C.1.5</b> Converting a numerical variable to a categorical one</a></li>
<li class="chapter" data-level="C.1.6" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-prop"><i class="fa fa-check"></i><b>C.1.6</b> Computing proportions</a></li>
<li class="chapter" data-level="C.1.7" data-path="C-appendixC.html"><a href="C-appendixC.html#appendix-commas"><i class="fa fa-check"></i><b>C.1.7</b> Dealing with %, commas, and $</a></li>
</ul></li>
<li class="chapter" data-level="C.2" data-path="C-appendixC.html"><a href="C-appendixC.html#interactive-graphics"><i class="fa fa-check"></i><b>C.2</b> Interactive graphics</a>
<ul>
<li class="chapter" data-level="C.2.1" data-path="C-appendixC.html"><a href="C-appendixC.html#interactive-linegraphs"><i class="fa fa-check"></i><b>C.2.1</b> Interactive linegraphs</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="D" data-path="D-appendixD.html"><a href="D-appendixD.html"><i class="fa fa-check"></i><b>D</b> Learning Check Solutions</a>
<ul>
<li class="chapter" data-level="D.1" data-path="D-appendixD.html"><a href="D-appendixD.html#chapter-1-solutions"><i class="fa fa-check"></i><b>D.1</b> Chapter 1 Solutions</a></li>
</ul></li>
<li class="chapter" data-level="E" data-path="E-appendixE.html"><a href="E-appendixE.html"><i class="fa fa-check"></i><b>E</b> Versions of R Packages Used</a></li>
<li class="chapter" data-level="" data-path="references.html"><a href="references.html"><i class="fa fa-check"></i>References</a></li>
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<div id="inference-for-regression" class="section level1" number="10">
<h1><span class="header-section-number">Chapter 10</span> Inference for Regression</h1>
<p>In our penultimate chapter, we’ll revisit the regression models we first studied in Chapters <a href="5-regression.html#regression">5</a> and <a href="6-multiple-regression.html#multiple-regression">6</a>. Armed with our knowledge of confidence intervals and hypothesis tests from Chapters <a href="8-confidence-intervals.html#confidence-intervals">8</a> and <a href="9-hypothesis-testing.html#hypothesis-testing">9</a>, we’ll be able to apply statistical inference to further our understanding of relationships between outcome and explanatory variables.</p>
<div id="inf-packages" class="section level3 unnumbered">
<h3>Needed packages</h3>
<p>Let’s load all the packages needed for this chapter (this assumes you’ve already installed them). Recall from our discussion in Section <a href="4-tidy.html#tidyverse-package">4.4</a> that loading the <code>tidyverse</code> package by running <code>library(tidyverse)</code> loads the following commonly used data science packages all at once:</p>
<ul>
<li><code>ggplot2</code> for data visualization</li>
<li><code>dplyr</code> for data wrangling</li>
<li><code>tidyr</code> for converting data to “tidy” format</li>
<li><code>readr</code> for importing spreadsheet data into R</li>
<li>As well as the more advanced <code>purrr</code>, <code>tibble</code>, <code>stringr</code>, and <code>forcats</code> packages</li>
</ul>
<p>If needed, read Section <a href="1-getting-started.html#packages">1.3</a> for information on how to install and load R packages.</p>
<div class="sourceCode" id="cb401"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb401-1"><a href="10-inference-for-regression.html#cb401-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb401-2"><a href="10-inference-for-regression.html#cb401-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(moderndive)</span>
<span id="cb401-3"><a href="10-inference-for-regression.html#cb401-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(infer)</span>
<span id="cb401-4"><a href="10-inference-for-regression.html#cb401-4" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(abd)</span></code></pre></div>
</div>
<div id="regression-refresher" class="section level2" number="10.1">
<h2><span class="header-section-number">10.1</span> Regression refresher</h2>
<p>Before jumping into inference for regression, let’s remind ourselves of the study to estimate lion ages based on nose coloration in Section <a href="5-regression.html#model1">5.1</a>.</p>
<div id="lion-age-and-nose-coloration" class="section level3" number="10.1.1">
<h3><span class="header-section-number">10.1.1</span> Lion age and nose coloration</h3>
<p>Recall using simple linear regression we modeled the relationship between</p>
<ol style="list-style-type: decimal">
<li>A numerical outcome variable <span class="math inline">\(y\)</span> (proportion of the nose that’s black) and</li>
<li>A single numerical explanatory variable <span class="math inline">\(x\)</span> (lion’s age).</li>
</ol>
<p>We started with the <code>LionNoses</code> data frame in the <code>abd</code> package, which contained the two variables of interest: <code>age</code> and <code>proportion.black</code>:</p>
<div class="sourceCode" id="cb402"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb402-1"><a href="10-inference-for-regression.html#cb402-1" aria-hidden="true" tabindex="-1"></a>LionNoses</span></code></pre></div>
<pre><code> age proportion.black
1 1.1 0.21
2 1.5 0.14
3 1.9 0.11
4 2.2 0.13
5 2.6 0.12
6 3.2 0.13
7 3.2 0.12
8 2.9 0.18
9 2.4 0.23
10 2.1 0.22
11 1.9 0.20
12 1.9 0.17
13 1.9 0.15
14 1.9 0.27
15 2.8 0.26
16 3.6 0.21
17 4.3 0.30
18 3.8 0.42
19 4.2 0.43
20 5.4 0.59
21 5.8 0.60
22 6.0 0.72
23 3.4 0.29
24 4.0 0.10
25 7.3 0.48
26 7.3 0.44
27 7.8 0.34
28 7.1 0.37
29 7.1 0.34
30 13.1 0.74
31 8.8 0.79
32 5.4 0.51</code></pre>
<p>In Subsection <a href="5-regression.html#model1EDA">5.1.1</a>, we performed an exploratory data analysis of the relationship between these two variables of <code>age</code> and <code>proportion.black</code>. We saw there that a clearly positive correlation of 0.79 existed between the two variables.</p>
<p>This was evidenced in Figure <a href="10-inference-for-regression.html#fig:regline">10.1</a> of the scatterplot along with the “best-fitting” regression line that summarizes the linear relationship between the two variables of <code>proportion.black</code> and <code>age</code>. Recall in Subsection <a href="5-regression.html#leastsquares">5.3.2</a> that we defined a “best-fitting” line as the line that minimizes the <em>sum of squared residuals</em>.</p>
<div class="sourceCode" id="cb404"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb404-1"><a href="10-inference-for-regression.html#cb404-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(LionNoses, </span>
<span id="cb404-2"><a href="10-inference-for-regression.html#cb404-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">aes</span>(<span class="at">x =</span> age, <span class="at">y =</span> proportion.black)) <span class="sc">+</span></span>
<span id="cb404-3"><a href="10-inference-for-regression.html#cb404-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb404-4"><a href="10-inference-for-regression.html#cb404-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">x =</span> <span class="st">"Age (years)"</span>, </span>
<span id="cb404-5"><a href="10-inference-for-regression.html#cb404-5" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="st">"Proportion of black nose"</span>,</span>
<span id="cb404-6"><a href="10-inference-for-regression.html#cb404-6" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Scatterplot of relationship of relative coloration and age of male lions."</span>) <span class="sc">+</span> </span>
<span id="cb404-7"><a href="10-inference-for-regression.html#cb404-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>(<span class="at">method =</span> <span class="st">"lm"</span>, <span class="at">se =</span> <span class="cn">FALSE</span>)</span></code></pre></div>
<div class="figure" style="text-align: center"><span style="display:block;" id="fig:regline"></span>
<img src="ModernDive_files/figure-html/regline-1.png" alt="Relationship with regression line." width="\textwidth" />
<p class="caption">
FIGURE 10.1: Relationship with regression line.
</p>
</div>
<p>Looking at this plot again, you can see that the line has a positive slope, increasing from left to right as the <code>age</code> variable increases, but by how much? To get to this information, recall that we followed a two-step procedure:</p>
<ol style="list-style-type: decimal">
<li>We first “fit” the linear regression model using the <code>lm()</code> function with the formula <code>proportion.black ~ age</code>. We saved this model in <code>lion_model</code>.</li>
<li>We get the regression table by applying the <code>get_regression_table()</code> function from the <code>moderndive</code> package to <code>lion_model</code>.</li>
</ol>
<div class="sourceCode" id="cb405"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb405-1"><a href="10-inference-for-regression.html#cb405-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Fit regression model:</span></span>
<span id="cb405-2"><a href="10-inference-for-regression.html#cb405-2" aria-hidden="true" tabindex="-1"></a>lion_model <span class="ot"><-</span> <span class="fu">lm</span>(proportion.black <span class="sc">~</span> age, <span class="at">data =</span> LionNoses)</span>
<span id="cb405-3"><a href="10-inference-for-regression.html#cb405-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Get regression table:</span></span>
<span id="cb405-4"><a href="10-inference-for-regression.html#cb405-4" aria-hidden="true" tabindex="-1"></a><span class="fu">get_regression_table</span>(lion_model)</span></code></pre></div>
<table class="table" style="font-size: 16px; margin-left: auto; margin-right: auto;">
<caption style="font-size: initial !important;">
<span id="tab:regtable-11">TABLE 10.1: </span>Previously seen linear regression table
</caption>
<thead>
<tr>
<th style="text-align:left;">
term
</th>
<th style="text-align:right;">
estimate
</th>
<th style="text-align:right;">
std_error
</th>
<th style="text-align:right;">
statistic
</th>
<th style="text-align:right;">
p_value
</th>
<th style="text-align:right;">
lower_ci
</th>
<th style="text-align:right;">
upper_ci
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
intercept
</td>
<td style="text-align:right;">
0.070
</td>
<td style="text-align:right;">
0.042
</td>
<td style="text-align:right;">
1.66
</td>
<td style="text-align:right;">
0.107
</td>
<td style="text-align:right;">
-0.016
</td>
<td style="text-align:right;">
0.155
</td>
</tr>
<tr>
<td style="text-align:left;">
age
</td>
<td style="text-align:right;">
0.059
</td>
<td style="text-align:right;">
0.008
</td>
<td style="text-align:right;">
7.05
</td>
<td style="text-align:right;">
0.000
</td>
<td style="text-align:right;">
0.042
</td>
<td style="text-align:right;">
0.076
</td>
</tr>
</tbody>
</table>
<p>Using the values in the <code>estimate</code> column of the resulting regression table in Table <a href="10-inference-for-regression.html#tab:regtable-11">10.1</a>, we could then obtain the equation of the “best-fitting” regression line in Figure <a href="10-inference-for-regression.html#fig:regline">10.1</a>:</p>
<p><span class="math display">\[
\begin{aligned}
\widehat{y} &= b_0 + b_1 \cdot x\\
\widehat{\text{proportion.black}} &= b_0 + b_{\text{age}} \cdot\text{age}\\
&= 0.070 + 0.059\cdot\text{age}
\end{aligned}
\]</span></p>
<p>where <span class="math inline">\(b_0\)</span> is the fitted intercept and <span class="math inline">\(b_1\)</span> is the fitted slope for <code>age</code>. Recall the interpretation of the <span class="math inline">\(b_1\)</span> = 0.059 value of the fitted slope:</p>
<blockquote>
<p>For every increase of one unit in lion age, there is an associated increase, on average, of 0.059 units of the black proportion of the nose.</p>
</blockquote>
<p>Thus, the slope value quantifies the relationship between the <span class="math inline">\(y\)</span> variable <code>proportion.black</code> and the <span class="math inline">\(x\)</span> variable <code>age</code>. We also discussed the intercept value of <span class="math inline">\(b_0\)</span> = 0.07 and its lack of practical interpretation, since the range of ages doesn’t include 0.</p>
</div>
<div id="sampling-scenario-2" class="section level3" number="10.1.2">
<h3><span class="header-section-number">10.1.2</span> Sampling scenario</h3>
<p>Let’s now revisit this study in terms of the terminology and notation related to sampling we studied in Subsection <a href="7-sampling.html#terminology-and-notation">7.3.1</a>.</p>
<p>First, let’s view these 32 lions as a <em>representative sample</em> from a greater <em>study population</em>. In our case, let’s assume that the study population is <em>all</em> lions living in the wild and that this sample of 32 lions is a representative sample. Unfortunately, we can only <em>assume</em> these two facts without more knowledge of the <em>sampling methodology</em> used by the researchers.</p>
<p>Since we are viewing these <span class="math inline">\(n\)</span> = 32 lions as a sample, we can view our fitted slope <span class="math inline">\(b_1\)</span> = 0.059 as a <em>point estimate</em> of the <em>population slope</em> <span class="math inline">\(\beta_1\)</span>. In other words, <span class="math inline">\(\beta_1\)</span> quantifies the relationship between <code>proportion.black</code> and <code>age</code> for <em>all</em> lions in the wild. Similarly, we can view our fitted intercept <span class="math inline">\(b_0\)</span> = 0.07 as a <em>point estimate</em> of the <em>population intercept</em> <span class="math inline">\(\beta_0\)</span> for <em>all</em> lions in the wild.</p>
<p>Putting these two ideas together, we can view the equation of the fitted line <span class="math inline">\(\widehat{y}\)</span> = <span class="math inline">\(b_0 + b_1 \cdot x\)</span> = <span class="math inline">\(0.070 + 0.059 \cdot \text{age}\)</span> as an estimate of some true and unknown <em>population line</em> <span class="math inline">\(y = \beta_0 + \beta_1 \cdot x\)</span>. Thus we can draw parallels between our lion age analysis and all the sampling scenarios we’ve seen previously. In this chapter, we’ll focus on the final scenario of regression slopes as shown in Table <a href="10-inference-for-regression.html#tab:summarytable-ch11">10.2</a>.</p>
<table class="table" style="font-size: 16px; margin-left: auto; margin-right: auto;">
<caption style="font-size: initial !important;">
<span id="tab:summarytable-ch11">TABLE 10.2: </span>Scenarios of sampling for inference
</caption>
<thead>
<tr>
<th style="text-align:right;">
Scenario
</th>
<th style="text-align:left;">
Population parameter
</th>
<th style="text-align:left;">
Notation
</th>
<th style="text-align:left;">
Point estimate
</th>
<th style="text-align:left;">
Symbol(s)
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:right;width: 0.5in; ">
1
</td>
<td style="text-align:left;width: 0.7in; ">
Population proportion
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(p\)</span>
</td>
<td style="text-align:left;width: 1.1in; ">
Sample proportion
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\widehat{p}\)</span>
</td>
</tr>
<tr>
<td style="text-align:right;width: 0.5in; ">
2
</td>
<td style="text-align:left;width: 0.7in; ">
Population mean
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\mu\)</span>
</td>
<td style="text-align:left;width: 1.1in; ">
Sample mean
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\overline{x}\)</span> or <span class="math inline">\(\widehat{\mu}\)</span>
</td>
</tr>
<tr>
<td style="text-align:right;width: 0.5in; ">
3
</td>
<td style="text-align:left;width: 0.7in; ">
Difference in population proportions
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(p_1 - p_2\)</span>
</td>
<td style="text-align:left;width: 1.1in; ">
Difference in sample proportions
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\widehat{p}_1 - \widehat{p}_2\)</span>
</td>
</tr>
<tr>
<td style="text-align:right;width: 0.5in; ">
4
</td>
<td style="text-align:left;width: 0.7in; ">
Difference in population means
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\mu_1 - \mu_2\)</span>
</td>
<td style="text-align:left;width: 1.1in; ">
Difference in sample means
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\overline{x}_1 - \overline{x}_2\)</span>
</td>
</tr>
<tr>
<td style="text-align:right;width: 0.5in; ">
5
</td>
<td style="text-align:left;width: 0.7in; ">
Population regression slope
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(\beta_1\)</span>
</td>
<td style="text-align:left;width: 1.1in; ">
Fitted regression slope
</td>
<td style="text-align:left;width: 1in; ">
<span class="math inline">\(b_1\)</span> or <span class="math inline">\(\widehat{\beta}_1\)</span>
</td>
</tr>
</tbody>
</table>
<p>Since we are now viewing our fitted slope <span class="math inline">\(b_1\)</span> and fitted intercept <span class="math inline">\(b_0\)</span> as <em>point estimates</em> based on a <em>sample</em>, these estimates will again be subject to <em>sampling variability</em>. In other words, if we collected a new sample of data on a different set of <span class="math inline">\(n\)</span> = 32 lions, the new fitted slope <span class="math inline">\(b_1\)</span> will likely differ from 0.059. The same goes for the new fitted intercept <span class="math inline">\(b_0\)</span>. But by how much will these estimates <em>vary</em>? This information is in the remaining columns of the regression table in Table <a href="10-inference-for-regression.html#tab:regtable-11">10.1</a>. Our knowledge of sampling from Chapter <a href="7-sampling.html#sampling">7</a>, confidence intervals from Chapter <a href="8-confidence-intervals.html#confidence-intervals">8</a>, and hypothesis tests from Chapter <a href="9-hypothesis-testing.html#hypothesis-testing">9</a> will help us interpret these remaining columns.</p>
</div>
</div>
<div id="regression-interp" class="section level2" number="10.2">
<h2><span class="header-section-number">10.2</span> Interpreting regression tables</h2>
<p>We’ve so far focused only on the two leftmost columns of the regression table in Table <a href="10-inference-for-regression.html#tab:regtable-11">10.1</a>: <code>term</code> and <code>estimate</code>. Let’s now shift our attention to the remaining columns: <code>std_error</code>, <code>statistic</code>, <code>p_value</code>, <code>lower_ci</code> and <code>upper_ci</code> in Table @ref(tab:proportion.black-model-part-deux).</p>
<table class="table" style="font-size: 16px; margin-left: auto; margin-right: auto;">
<caption style="font-size: initial !important;">
(#tab:proportion.black-model-part-deux)Previously seen regression table
</caption>
<thead>
<tr>
<th style="text-align:left;">
term
</th>
<th style="text-align:right;">
estimate
</th>
<th style="text-align:right;">
std_error
</th>
<th style="text-align:right;">
statistic
</th>
<th style="text-align:right;">
p_value
</th>
<th style="text-align:right;">
lower_ci
</th>