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<h2 id="toc-title">Contents</h2>
<ul>
<li><a href="#group-members" id="toc-group-members" class="nav-link active" data-scroll-target="#group-members"><span class="header-section-number">1</span> <strong>Group members:</strong></a></li>
<li><a href="#workflow" id="toc-workflow" class="nav-link" data-scroll-target="#workflow"><span class="header-section-number">2</span> <strong>Workflow</strong></a></li>
<li><a href="#introduction" id="toc-introduction" class="nav-link" data-scroll-target="#introduction"><span class="header-section-number">3</span> <strong>Introduction</strong></a></li>
<li><a href="#research-question" id="toc-research-question" class="nav-link" data-scroll-target="#research-question"><span class="header-section-number">4</span> <strong>Research question</strong></a></li>
<li><a href="#methodology" id="toc-methodology" class="nav-link" data-scroll-target="#methodology"><span class="header-section-number">5</span> <strong>Methodology</strong></a></li>
<li><a href="#data-exploration" id="toc-data-exploration" class="nav-link" data-scroll-target="#data-exploration"><span class="header-section-number">6</span> <strong>Data Exploration</strong></a>
<ul class="collapse">
<li><a href="#load-and-inspect-the-data" id="toc-load-and-inspect-the-data" class="nav-link" data-scroll-target="#load-and-inspect-the-data"><span class="header-section-number">6.1</span> <strong>Load and inspect the data</strong></a></li>
<li><a href="#data-preparation" id="toc-data-preparation" class="nav-link" data-scroll-target="#data-preparation"><span class="header-section-number">6.2</span> <strong>Data preparation</strong></a></li>
<li><a href="#exploratory-data-analysis-eda" id="toc-exploratory-data-analysis-eda" class="nav-link" data-scroll-target="#exploratory-data-analysis-eda"><span class="header-section-number">6.3</span> <strong>Exploratory data analysis (EDA)</strong></a></li>
<li><a href="#data-summary" id="toc-data-summary" class="nav-link" data-scroll-target="#data-summary"><span class="header-section-number">6.4</span> <strong>Data Summary</strong></a></li>
<li><a href="#data-visualization" id="toc-data-visualization" class="nav-link" data-scroll-target="#data-visualization"><span class="header-section-number">6.5</span> <strong>Data Visualization</strong></a></li>
</ul></li>
<li><a href="#perform-linear-regression-model" id="toc-perform-linear-regression-model" class="nav-link" data-scroll-target="#perform-linear-regression-model"><span class="header-section-number">7</span> <strong>Perform Linear Regression Model</strong></a>
<ul class="collapse">
<li><a href="#univariable-analysis" id="toc-univariable-analysis" class="nav-link" data-scroll-target="#univariable-analysis"><span class="header-section-number">7.1</span> <strong>Univariable analysis</strong></a></li>
<li><a href="#multiple-linear-regression-without-interaction-model-a" id="toc-multiple-linear-regression-without-interaction-model-a" class="nav-link" data-scroll-target="#multiple-linear-regression-without-interaction-model-a"><span class="header-section-number">7.2</span> Multiple Linear Regression without Interaction (Model A)</a></li>
<li><a href="#multiple-linear-regression-with-interaction-model-b" id="toc-multiple-linear-regression-with-interaction-model-b" class="nav-link" data-scroll-target="#multiple-linear-regression-with-interaction-model-b"><span class="header-section-number">7.3</span> Multiple Linear Regression with Interaction (Model B)</a></li>
</ul></li>
<li><a href="#model-selection" id="toc-model-selection" class="nav-link" data-scroll-target="#model-selection"><span class="header-section-number">8</span> <strong>Model Selection</strong></a></li>
<li><a href="#model-diagnostic-and-assumption-checking" id="toc-model-diagnostic-and-assumption-checking" class="nav-link" data-scroll-target="#model-diagnostic-and-assumption-checking"><span class="header-section-number">9</span> <strong>Model Diagnostic and Assumption Checking</strong></a></li>
<li><a href="#final-model-checking" id="toc-final-model-checking" class="nav-link" data-scroll-target="#final-model-checking"><span class="header-section-number">10</span> <strong>Final Model Checking</strong></a>
<ul class="collapse">
<li><a href="#fitted-values-and-residuals" id="toc-fitted-values-and-residuals" class="nav-link" data-scroll-target="#fitted-values-and-residuals"><span class="header-section-number">10.1</span> <strong>Fitted values and residuals</strong></a></li>
<li><a href="#influential-observations" id="toc-influential-observations" class="nav-link" data-scroll-target="#influential-observations"><span class="header-section-number">10.2</span> <strong>Influential Observations</strong></a></li>
<li><a href="#model-diagnostics-and-assumption-checking-for-final-model" id="toc-model-diagnostics-and-assumption-checking-for-final-model" class="nav-link" data-scroll-target="#model-diagnostics-and-assumption-checking-for-final-model"><span class="header-section-number">10.3</span> <strong>Model diagnostics and assumption checking for final model</strong></a></li>
</ul></li>
<li><a href="#final-table-for-multiple-linear-regression" id="toc-final-table-for-multiple-linear-regression" class="nav-link" data-scroll-target="#final-table-for-multiple-linear-regression"><span class="header-section-number">11</span> <strong>Final table for multiple linear regression</strong></a></li>
<li><a href="#interpretation" id="toc-interpretation" class="nav-link" data-scroll-target="#interpretation"><span class="header-section-number">12</span> <strong>Interpretation</strong></a></li>
<li><a href="#github-repo" id="toc-github-repo" class="nav-link" data-scroll-target="#github-repo"><span class="header-section-number">13</span> <strong>Github Repo</strong></a></li>
</ul>
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<div class="quarto-title">
<h1 class="title">Assignment Multiple Linear Regression</h1>
</div>
<div class="quarto-title-meta">
<div>
<div class="quarto-title-meta-heading">Author</div>
<div class="quarto-title-meta-contents">
<p>Group 1 </p>
</div>
</div>
</div>
</header>
<section id="group-members" class="level2" data-number="1">
<h2 data-number="1" class="anchored" data-anchor-id="group-members"><span class="header-section-number">1</span> <strong>Group members:</strong></h2>
<p>1) Muhammad Ruhaifi bin Muhammad Sabri (22305762)</p>
<p>2) Dzul Hairy bin Mohd Ramlan (22305758)</p>
<p>3) Nur Shuhaiza binti Supian (22306056)</p>
<p>4) Aziemah binti Nafsun (22305774)</p>
<p>5) Noor Nazli bt Din (22306061)</p>
<hr>
</section>
<section id="workflow" class="level2" data-number="2">
<h2 data-number="2" class="anchored" data-anchor-id="workflow"><span class="header-section-number">2</span> <strong>Workflow</strong></h2>
<ul>
<li><p>Introduction</p></li>
<li><p>Research question</p></li>
<li><p>Methodology</p></li>
<li><p>Data Exploration</p></li>
<li><p>Perform Linear Regression Model</p></li>
<li><p>Model Selection</p></li>
<li><p>Model Diagnostic and Assumption Checking</p></li>
<li><p>Final Model Checking</p></li>
<li><p>Final Table Presentation</p></li>
<li><p>Interpretation</p></li>
</ul>
<hr>
</section>
<section id="introduction" class="level2" data-number="3">
<h2 data-number="3" class="anchored" data-anchor-id="introduction"><span class="header-section-number">3</span> <strong>Introduction</strong></h2>
<p>This was data from <strong>US Health Insurance Dataset</strong> comprise medical information and costs billed by health insurance companies. it contains six variables with 1338 observations:</p>
<ol type="1">
<li>age: age of patient (continuous)</li>
<li>sex: gender of the subjects (categorical : male, female)</li>
<li>bmi: BMI of subject (continuous)</li>
<li>children: Number of children covered by health insurance (continuous)</li>
<li>smoker: smoking status of subject (categorical: no, yes)</li>
<li>charges: individual medical costs billed by health insurance (continuous)</li>
</ol>
<hr>
</section>
<section id="research-question" class="level2" data-number="4">
<h2 data-number="4" class="anchored" data-anchor-id="research-question"><span class="header-section-number">4</span> <strong>Research question</strong></h2>
<p>How are age, BMI, number of children, sex, and smoking status associated with health insurance costs (charges) in USD?</p>
<hr>
</section>
<section id="methodology" class="level2" data-number="5">
<h2 data-number="5" class="anchored" data-anchor-id="methodology"><span class="header-section-number">5</span> <strong>Methodology</strong></h2>
<p>We will use multiple linear regression model approach to analyse predictors to explain variation of health insurance cost in sample population. 1st model will consist of all independent variables (age, sex, BMI, children, and smoking status) and another model will be constructed by adding interaction term between age and smoking status as effect of age towards health insurance cost can be modified by individual’s smoking status. Model comparison will be executed using anova test to select the final model. Model assessment will be conducted by running the diagnostic plot and checking the model for any influential observation before final model is concluded.</p>
<hr>
</section>
<section id="data-exploration" class="level2" data-number="6">
<h2 data-number="6" class="anchored" data-anchor-id="data-exploration"><span class="header-section-number">6</span> <strong>Data Exploration</strong></h2>
<div class="cell">
<details class="code-fold">
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co">#loading necessary packages</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(haven)</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(gtsummary)</span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(corrplot)</span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(knitr)</span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyr)</span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2)</span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(broom)</span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(sjPlot)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
<section id="load-and-inspect-the-data" class="level3" data-number="6.1">
<h3 data-number="6.1" class="anchored" data-anchor-id="load-and-inspect-the-data"><span class="header-section-number">6.1</span> <strong>Load and inspect the data</strong></h3>
<div class="cell">
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Load the dataset</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(readr)</span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>insurance <span class="ot"><-</span> <span class="fu">read_csv</span>(<span class="st">"insurance.csv"</span>)</span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Inspect the data</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a><span class="fu">str</span>(insurance)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>spc_tbl_ [1,338 × 6] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ age : num [1:1338] 19 18 28 33 32 31 46 37 37 60 ...
$ sex : chr [1:1338] "female" "male" "male" "male" ...
$ bmi : num [1:1338] 27.9 33.8 33 22.7 28.9 ...
$ children: num [1:1338] 0 1 3 0 0 0 1 3 2 0 ...
$ smoker : chr [1:1338] "yes" "no" "no" "no" ...
$ charges : num [1:1338] 16885 1726 4449 21984 3867 ...
- attr(*, "spec")=
.. cols(
.. age = col_double(),
.. sex = col_character(),
.. bmi = col_double(),
.. children = col_double(),
.. smoker = col_character(),
.. charges = col_double()
.. )
- attr(*, "problems")=<externalptr> </code></pre>
</div>
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="fu">summary</span>(insurance)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stdout">
<pre><code> age sex bmi children
Min. :18.00 Length:1338 Min. :15.96 Min. :0.000
1st Qu.:27.00 Class :character 1st Qu.:26.30 1st Qu.:0.000
Median :39.00 Mode :character Median :30.40 Median :1.000
Mean :39.21 Mean :30.66 Mean :1.095
3rd Qu.:51.00 3rd Qu.:34.69 3rd Qu.:2.000
Max. :64.00 Max. :53.13 Max. :5.000
smoker charges
Length:1338 Min. : 1122
Class :character 1st Qu.: 4740
Mode :character Median : 9382
Mean :13270
3rd Qu.:16640
Max. :63770 </code></pre>
</div>
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(insurance)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code># A tibble: 6 × 6
age sex bmi children smoker charges
<dbl> <chr> <dbl> <dbl> <chr> <dbl>
1 19 female 27.9 0 yes 16885.
2 18 male 33.8 1 no 1726.
3 28 male 33 3 no 4449.
4 33 male 22.7 0 no 21984.
5 32 male 28.9 0 no 3867.
6 31 female 25.7 0 no 3757.</code></pre>
</div>
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Check for missing values</span></span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a><span class="fu">sum</span>(<span class="fu">is.na</span>(insurance))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>[1] 0</code></pre>
</div>
</div>
<hr>
</section>
<section id="data-preparation" class="level3" data-number="6.2">
<h3 data-number="6.2" class="anchored" data-anchor-id="data-preparation"><span class="header-section-number">6.2</span> <strong>Data preparation</strong></h3>
<p>Convert categorical variables (<code>sex</code> and <code>smoker</code>) to factors:</p>
<div class="cell">
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<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb10"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>insurance<span class="sc">$</span>sex <span class="ot"><-</span> <span class="fu">as.factor</span>(insurance<span class="sc">$</span>sex)</span>
<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>insurance<span class="sc">$</span>smoker <span class="ot"><-</span> <span class="fu">as.factor</span>(insurance<span class="sc">$</span>smoker)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
</div>
<p>Check if levels are correct:</p>
<div class="cell">
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<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="fu">levels</span>(insurance<span class="sc">$</span>sex)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<div class="cell-output cell-output-stdout">
<pre><code>[1] "female" "male" </code></pre>
</div>
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="fu">levels</span>(insurance<span class="sc">$</span>smoker)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output cell-output-stdout">
<pre><code>[1] "no" "yes"</code></pre>
</div>
</div>
</section>
<section id="exploratory-data-analysis-eda" class="level3" data-number="6.3">
<h3 data-number="6.3" class="anchored" data-anchor-id="exploratory-data-analysis-eda"><span class="header-section-number">6.3</span> <strong>Exploratory data analysis (EDA)</strong></h3>
<p><strong>Visualise relationships:</strong></p>
<div class="cell">
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb15"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="fu">pairs</span>(insurance[, <span class="fu">c</span>(<span class="st">"age"</span>, <span class="st">"bmi"</span>, <span class="st">"children"</span>, <span class="st">"charges"</span>)])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Multiple-Linear-Regression-Assignment_files/figure-html/unnamed-chunk-5-1.png" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
<p><strong>Correlation between continuous variables:</strong></p>
<div class="cell">
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<div class="sourceCode cell-code" id="cb16"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a>cor_matrix <span class="ot"><-</span> <span class="fu">cor</span>(insurance[, <span class="fu">c</span>(<span class="st">"age"</span>, <span class="st">"bmi"</span>, <span class="st">"children"</span>, <span class="st">"charges"</span>)])</span>
<span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a><span class="co">#visualize the correlation matrix</span></span>
<span id="cb16-4"><a href="#cb16-4" aria-hidden="true" tabindex="-1"></a><span class="fu">corrplot</span>(cor_matrix, <span class="at">method =</span> <span class="st">"circle"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Multiple-Linear-Regression-Assignment_files/figure-html/unnamed-chunk-6-1.png" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
<p>no obvious correlation issue between continuous variables</p>
<p><strong>Boxplots for categorical variables:</strong></p>
<ol type="1">
<li><strong>smoking status</strong></li>
</ol>
<div class="cell">
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb17"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(insurance, <span class="fu">aes</span>(<span class="at">x =</span> smoker, <span class="at">y =</span> charges, <span class="at">fill =</span> smoker)) <span class="sc">+</span></span>
<span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>() <span class="sc">+</span></span>
<span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Health Insurance Cost by Smoking Status"</span>, <span class="at">y =</span> <span class="st">"Charges (USD)"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Multiple-Linear-Regression-Assignment_files/figure-html/unnamed-chunk-7-1.png" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div>
<ol start="2" type="1">
<li><p><strong>gender</strong></p>
<div class="cell">
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<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(insurance, <span class="fu">aes</span>(<span class="at">x =</span> sex, <span class="at">y =</span> charges, <span class="at">fill =</span> sex)) <span class="sc">+</span></span>
<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>() <span class="sc">+</span></span>
<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Health Insurance Cost by Gender"</span>, <span class="at">y =</span> <span class="st">"Charges (USD)"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Multiple-Linear-Regression-Assignment_files/figure-html/unnamed-chunk-8-1.png" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>
</div></li>
</ol>
</section>
<section id="data-summary" class="level3" data-number="6.4">
<h3 data-number="6.4" class="anchored" data-anchor-id="data-summary"><span class="header-section-number">6.4</span> <strong>Data Summary</strong></h3>
<p><strong>Table Summary</strong></p>
<div class="cell">
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<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>insurance <span class="sc">%>%</span> </span>
<span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">tbl_summary</span>( <span class="at">label =</span> <span class="fu">list</span>(age <span class="sc">~</span> <span class="st">"Age"</span>, sex <span class="sc">~</span> <span class="st">"Gender"</span>, bmi <span class="sc">~</span> <span class="st">"BMI"</span> , children <span class="sc">~</span> <span class="st">"Number of Children"</span>, smoker <span class="sc">~</span> <span class="st">"Smoking Status"</span>, charges <span class="sc">~</span> <span class="st">"Health Insurance Cost (USD)"</span>) , </span>
<span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a> <span class="at">statistic =</span> <span class="fu">list</span>(<span class="fu">all_continuous</span>() <span class="sc">~</span> <span class="st">"{mean} ({sd})"</span>)) <span class="sc">%>%</span> <span class="fu">bold_labels</span>() <span class="sc">%>%</span> </span>
<span id="cb19-4"><a href="#cb19-4" aria-hidden="true" tabindex="-1"></a><span class="fu">italicize_levels</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
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</style>
<table class="gt_table caption-top table table-sm table-striped small" data-quarto-postprocess="true" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
<colgroup>
<col style="width: 50%">
<col style="width: 50%">
</colgroup>
<thead>
<tr class="header gt_col_headings">
<th id="label" class="gt_col_heading gt_columns_bottom_border gt_left" data-quarto-table-cell-role="th" scope="col"><strong>Characteristic</strong></th>
<th id="stat_0" class="gt_col_heading gt_columns_bottom_border gt_center" data-quarto-table-cell-role="th" scope="col"><strong>N = 1,338</strong><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span></th>
</tr>
</thead>
<tbody class="gt_table_body">
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">Age</td>
<td class="gt_row gt_center" headers="stat_0">39 (14)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">Gender</td>
<td class="gt_row gt_center" headers="stat_0"><br>
</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> female</td>
<td class="gt_row gt_center" headers="stat_0">662 (49%)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> male</td>
<td class="gt_row gt_center" headers="stat_0">676 (51%)</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">BMI</td>
<td class="gt_row gt_center" headers="stat_0">30.7 (6.1)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">Number of Children</td>
<td class="gt_row gt_center" headers="stat_0"><br>
</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 0</td>
<td class="gt_row gt_center" headers="stat_0">574 (43%)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 1</td>
<td class="gt_row gt_center" headers="stat_0">324 (24%)</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 2</td>
<td class="gt_row gt_center" headers="stat_0">240 (18%)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 3</td>
<td class="gt_row gt_center" headers="stat_0">157 (12%)</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 4</td>
<td class="gt_row gt_center" headers="stat_0">25 (1.9%)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-style: italic"> 5</td>
<td class="gt_row gt_center" headers="stat_0">18 (1.3%)</td>
</tr>
<tr class="odd">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">Smoking Status</td>
<td class="gt_row gt_center" headers="stat_0">274 (20%)</td>
</tr>
<tr class="even">
<td class="gt_row gt_left" headers="label" style="font-weight: bold">Health Insurance Cost (USD)</td>
<td class="gt_row gt_center" headers="stat_0">13,270 (12,110)</td>
</tr>
</tbody><tfoot class="gt_footnotes">
<tr class="odd">
<td colspan="2" class="gt_footnote"><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span> Mean (SD); n (%)</td>
</tr>
</tfoot>
</table>
</div>
</div>
</div>
<hr>
</section>
<section id="data-visualization" class="level3" data-number="6.5">
<h3 data-number="6.5" class="anchored" data-anchor-id="data-visualization"><span class="header-section-number">6.5</span> <strong>Data Visualization</strong></h3>
<p>For <strong>continuous data</strong>: We employ histograms to gain insight into the distribution of each feature. This allows us to understand the central tendency, spread, and shape of the dataset’s distribution.</p>
<ol type="1">
<li><p><strong>Age</strong></p>
<div class="cell">
<details class="code-fold">
<summary>Show the Code</summary>
<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(insurance, <span class="fu">aes</span> (age))<span class="sc">+</span></span>
<span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_histogram</span>()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</details>
<div class="cell-output-display">
<div>
<figure class="figure">
<p><img src="Multiple-Linear-Regression-Assignment_files/figure-html/unnamed-chunk-10-1.png" class="img-fluid figure-img" width="672"></p>
</figure>
</div>
</div>