Study guide with Analysing Data using Linear Models by Van den Berg - 2023/2024

Study guide with Analysing Data using Linear Models

Oline summaries and study assistance with the 2022 edition of Analysing Data using Linear Models by Van den Berg

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Bulletpoints per chapter with the 2022 edition of Analysing Data using Linear Models by van den Berg - Chapter
Summaries per chapter with the 2022 edition of Analysing Data using Linear Models by Van den Berg

Summaries per chapter with the 2022 edition of Analysing Data using Linear Models by Van den Berg

Summaries per chapter with the 2022 edition of Analysing Data using Linear Models by Van den Berg

What are variables, variation and co-variation? - Chapter 1
How can we make inferences about a mean? - Chapter 2
How can we make inferences about proportions? - Chapter 3
What does linear modelling entail? - Chapter 4
How can we make inferences about linear models? - Chapter 5
What are categorical predictor variables? - Chapter 6
What are the assumptions of linear models? - Chapter 7
What should we do when the assumptions are not met? - Chapter 8
What does moderation entail? - Chapter 9
How do researchers use contrast in statistical analysis? - Chapter 10
How do we perform post hoc comparisons? - Chapter 11
How do we perform linear mixed modelling? - Chapter 12
How do we conduct linear mixed models for more than two measurements? - Chapter 13
What are non-parametric alternatives for linear mixed models? - Chapter 14
How is logistic regression conducted with generalised linear models? - Chapter 15
How can generalised linear models be used for count data? - Chapter 16
What does big data analytics entail? - Chapter 17
Examtickets per chapter with the 2022 edition of Analysing Data using Linear Models by van den Berg - Chapter
Examtickets per chapter with the 2022 edition of Analysing Data using Linear Models by van den Berg - Chapter
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