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Summary of Analysing Data using Linear Models by Van den Berg - 2022 edition

Summaries per chapter with Analysing Data using Linear Models

Summaries per chapter with Analysing Data using Linear Models

  • For summaries with all chapters of the 2022 edition of Analysing Data using Linear Models by Van den Berg, see the supporting content of this page

Table of content

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

Related summaries and study assistance

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