DS Unit 1 Sprint 3
Welcome to Sprint 3
In this sprint, you'll learn about linear regression inference, multiple regression, linear algebra, and the bias-variance tradeoff. These foundations will help you understand how models work and how to interpret their results effectively.
You'll conduct hypothesis testing, understand how to interpret model outputs, explore vectors and matrices, and comprehend the essential balance between bias and variance in your models.
Modules
This sprint is structured to provide you with comprehensive knowledge of advanced regression techniques:
Module 1
Inference for Linear Regression
Learn how to identify appropriate hypotheses for testing statistical significance between quantitative variables, conduct t-tests for slope parameters, build confidence intervals, and identify assumption violations for linear regression.
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Multiple Regression
Explore how to model relationships with multiple predictor variables, conduct t-tests to determine variable significance, and compare model fit using adjusted R-squared.
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Linear Algebra
Define vectors and calculate length and dot products, understand cosine similarity between vectors, work with matrices, and use linear algebra to solve for linear regression coefficients.
View ModuleModule 4
Bias - Variance Tradeoff
Understand and define bias and variance, describe the tradeoff between them, and learn about different types of biases in modeling.
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