Multilevel

Multilevel model

Multilevel models are statistical models that account for parameters that vary at different levels. They are particularly useful for analyzing nested data, where individuals are grouped within higher-level units. These models can be used to analyze repeated measures and provide an alternative to ANCOVA for adjusting for covariates.

1 courses cover this concept

CS 61C Great Ideas in Computer Architecture (Machine Structures)

UC Berkeley

Fall 2022

This course deepens students' understanding of computer architecture and the translation of high-level programs into machine language. Emphasis is on C and assembly language programming, computer organization, parallelism, CPU design, and warehouse-scale computing. Prerequisites include CS61A and CS61B or equivalent C-based programming experience.

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