Research Methods Using R
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Research Methods Using R
Advanced Data Analysis in the Behavioural and Biological Sciences
Baker, Daniel H.
Oxford University Press
03/2022
352
Mole
Inglês
9780192896599
15 a 20 dias
690
Descrição não disponível.
1: Introduction
2: Introduction to the R environment
3: Cleaning and preparing data for analysis
4: Statistical tests as linear models
5: Power analysis
6: Meta-analysis
7: Mixed-effects models
8: Stochastic methods
9: Non-linear curve fitting
10: Fourier analysis
11: Multivariate t-tests
12: Structural equation modelling
13: Multidimensional scaling and k-means clustering
14: Multivariate pattern analysis
15: Correcting for multiple comparisons
16: Signal detection theory
17: Bayesian statistics
18: Plotting graphs and data visualisation
19: Reproducible data analysis
2: Introduction to the R environment
3: Cleaning and preparing data for analysis
4: Statistical tests as linear models
5: Power analysis
6: Meta-analysis
7: Mixed-effects models
8: Stochastic methods
9: Non-linear curve fitting
10: Fourier analysis
11: Multivariate t-tests
12: Structural equation modelling
13: Multidimensional scaling and k-means clustering
14: Multivariate pattern analysis
15: Correcting for multiple comparisons
16: Signal detection theory
17: Bayesian statistics
18: Plotting graphs and data visualisation
19: Reproducible data analysis
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
1: Introduction
2: Introduction to the R environment
3: Cleaning and preparing data for analysis
4: Statistical tests as linear models
5: Power analysis
6: Meta-analysis
7: Mixed-effects models
8: Stochastic methods
9: Non-linear curve fitting
10: Fourier analysis
11: Multivariate t-tests
12: Structural equation modelling
13: Multidimensional scaling and k-means clustering
14: Multivariate pattern analysis
15: Correcting for multiple comparisons
16: Signal detection theory
17: Bayesian statistics
18: Plotting graphs and data visualisation
19: Reproducible data analysis
2: Introduction to the R environment
3: Cleaning and preparing data for analysis
4: Statistical tests as linear models
5: Power analysis
6: Meta-analysis
7: Mixed-effects models
8: Stochastic methods
9: Non-linear curve fitting
10: Fourier analysis
11: Multivariate t-tests
12: Structural equation modelling
13: Multidimensional scaling and k-means clustering
14: Multivariate pattern analysis
15: Correcting for multiple comparisons
16: Signal detection theory
17: Bayesian statistics
18: Plotting graphs and data visualisation
19: Reproducible data analysis
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
