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      <title>Math 444 Stat Modeling Notes</title>
      <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes</link>
      <description>Last 10 notes on Math 444 Stat Modeling Notes</description>
      <generator>Quartz -- quartz.jzhao.xyz</generator>
      <item>
    <title>Class Notes stat modeling 15.10.26</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Class-Notes-stat-modeling-15.10.26</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Class-Notes-stat-modeling-15.10.26</guid>
    <description><![CDATA[  Midterm scope (test Tuesday, October 20, 2026): chapters 2, 3, and 5 — but not everything in them. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Exam 1</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Exam-1</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Exam-1</guid>
    <description><![CDATA[  Exam: Tuesday, October 20, 2026 Coverage: Chapter 2 (through 2.7), Chapter 3 (3.1–3.3), and Chapter 5 (5.1–5.3) — not dummy variables or analysis of covariance (see Class Notes stat modeling 15.10.26, which covers that material for reference only, not exam scope) Format: 50% R output (given output,... ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Fitting a Multiple Linear Regression</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Fitting-a-Multiple-Linear-Regression</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Fitting-a-Multiple-Linear-Regression</guid>
    <description><![CDATA[ Concepts A response often depends on more than one predictor, and using only one can leave out information that actually matters for explaining it. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Fitting a Simple Linear Regression</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Fitting-a-Simple-Linear-Regression</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Fitting-a-Simple-Linear-Regression</guid>
    <description><![CDATA[ Concepts We have observed pairs (x_i,y_i) and want one straight line that summarizes how Y changes with x. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Formula and Identity Sheet</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Formula-and-Identity-Sheet</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Formula-and-Identity-Sheet</guid>
    <description><![CDATA[  A one-page reference for the notation, identities, and assumptions that connect every note. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>MLR Inference, ANOVA, and Adjusted R-Squared</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/MLR-Inference,-ANOVA,-and-Adjusted-R-Squared</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/MLR-Inference,-ANOVA,-and-Adjusted-R-Squared</guid>
    <description><![CDATA[ Concepts With k predictors, the same SST=SS_{reg}+RSS decomposition from Residual and Sum-of-Squares Proofs still holds — the orthogonality that makes the cross term vanish comes from the normal equations, which hold in matrix form exactly as they did in SLR. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Partial F-Tests for Subsets of Predictors</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Partial-F-Tests-for-Subsets-of-Predictors</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Partial-F-Tests-for-Subsets-of-Predictors</guid>
    <description><![CDATA[ Concepts A partial F-test asks whether a whole group of predictors can be dropped at once, generalizing the individual coefficient t-test from one predictor to several simultaneously. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Reading R Regression Output</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Reading-R-Regression-Output</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Reading-R-Regression-Output</guid>
    <description><![CDATA[  Not a standalone exam question type on its own — it’s the presentation format any of the other problems could be posed in: “here’s summary(lm()) / anova() / a plot — answer this,” instead of a raw data table. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Regression Diagnostics and Leverage</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Regression-Diagnostics-and-Leverage</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Regression-Diagnostics-and-Leverage</guid>
    <description><![CDATA[ Concepts Regression calculations will always hand you a fitted line, even when a straight-line model is secretly the wrong choice for the data. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
  </item><item>
    <title>Regression Estimator Properties</title>
    <link>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Regression-Estimator-Properties</link>
    <guid>https://aaronjan98.github.io/Math-444-Stat-Modeling-Notes/Regression-Estimator-Properties</guid>
    <description><![CDATA[  Mean, variance, and covariance of the least-squares estimators, derived via covariance bilinearity. ]]></description>
    <pubDate>Sat, 17 Oct 2026 16:43:40 GMT</pubDate>
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