This class was created by Brainscape user Crystal Z. Visit their profile to learn more about the creator.
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Crystal Z
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Decks in this class (18)
1. Introduction to Linear Model
What is a model,
What are models represented as in...,
Why are models represented as fun...
15
cards
2. Multiple Regression
What is multiple regression,
What is multiple regression used for,
How would we interpret the interc...
11
cards
3. Testing and Evaluating Linear Models
What are the three parts of evalu...,
What question would ask to explor...,
How do we evaluate individual coe...
30
cards
4. F-Tests and Standardisation
How do we test significance of ov...,
What is an f test,
What is not sufficient to test th...
21
cards
5. Categorical Predictors
What is a categorical variable,
How should categorical variables ...,
What is meant by a binary variabl...
11
cards
6. Interactions: Categorical*Continuous
What is an interaction,
How is the slope impacted when th...,
What is a categorical continuous ...
12
cards
7. Interactions: Continuous*Continuous
What is the definition of a conti...,
What is mean centering,
What coefficient won t change whe...
23
cards
8. Interactions: Categorical*Categorical
What is a categorical categorical...,
When visualising a categorical ca...,
When visualising a categorical ca...
13
cards
9. Assumptions and Diagnostics
What are the different linear mod...,
What happens if assumptions are v...,
Why is it useful visualise assump...
36
cards
10. Model Comparisons
What is used to test if multiple ...,
How does an f test work,
How do we know through the f test...
14
cards
11. Effects Coding (Sum to Zero)
What is effects coding,
What is the issue of under identi...,
What fixes the issue of under ide...
9
cards
12. Coding Contrasts and F-Tests
What are the rules for manual con...,
What are the 9 different rules fo...,
What are orthogonal contrasts
15
cards
13. Simple Effects
What are main effects,
What are simple contrasts effects,
What are interactions
20
cards
14. Bootstrapping
What is bootstrapping,
What are assumption violations,
What are two possible explanation...
19
cards
15. Binary Logistic Model and Logistic Regression
What is logistic regression,
What is a binary outcome variable,
What is binary logistic regression
28
cards
16. Power Analysis
What is power,
Why is power important,
What are the different factors ef...
19
cards
17. Understanding Linear Models
What is causality,
What are the different conditions...,
How can causality be tested
38
cards
18. Exploratory and Confirmatory Data Analysis
When is should an exploratory ana...,
What are the issues with explorat...,
How can exploratory analysis be d...
23
cards
More about
DAPR 2 Em
- Class purpose General learning
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