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18.642 | Fall 2024 | Undergraduate

# Topics in Mathematics with Applications in Finance

This lecture provides a comprehensive overview of linear regression modeling, focusing on ordinary least squares (OLS) estimation, its mathematical formulation, and statistical properties. It discusses the derivation of the least squares estimator, the interpretation of the Hat matrix as a projection, the distributional assumptions under the normal linear model, inference using t- and F-tests, and model diagnostics including residual analysis and influence measures, concluding with extensions to generalized least squares for correlated errors.

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## Course Info

##### Instructors

- Dr. Peter Kempthorne
- Dr. Vasily Strela
- Dr. Jake Xia

##### Departments

- Mathematics

##### As Taught In

Fall 2024

##### Level

Undergraduate

##### Topics

- Business
  - Finance
- Mathematics
  - Applied Mathematics
  - Probability and Statistics

##### Learning Resource Types

notes Lecture Notes
theaters Lecture Videos
assignment Problem Sets
assignment Activity Assignments
group_work Projects
Readings

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