Difference between revisions of "An initial path towards statistical analysis"
From Sustainability Methods
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[[At least one categorical independent variable| | [[At least one categorical independent variable| | ||
More than 2 groups | More than 2 groups | ||
| − | [[https://sustainabilitymethods.org/index.php/Experiments#Analysis_of_Variance|Analysis of Variance]]<br> | + | [[https://sustainabilitymethods.org/index.php/Experiments#Analysis_of_Variance| Analysis of Variance]]<br> |
[[Dependent variable normally distributed|https://sustainabilitymethods.org/index.php/Data_distribution#The_normal_distribution]]<br> | [[Dependent variable normally distributed|https://sustainabilitymethods.org/index.php/Data_distribution#The_normal_distribution]]<br> | ||
[[Type II Anova|INSERT TYPE II]]<br> | [[Type II Anova|INSERT TYPE II]]<br> | ||
Revision as of 20:53, 11 January 2021
Start here with your data
Do you have several continuous variables without clear dependencies?
Yes-> Multivariate statistics
No-> Univariate statistics
Univariate statistics
Categorical and continuous data (?)
Categorical and continuous data
[[At least one categorical independent variable|
More than 2 groups
[Analysis of Variance]
https://sustainabilitymethods.org/index.php/Data_distribution#The_normal_distribution
INSERT TYPE II
INSERT RANDOM FACTOR
INSERT LMM
Dependent variable not normally distributed
Type III Anova
Dependent variable is count data
Dependent variable is 0/1 or proportions
Random factors
Generalized linear mixed effect models
Only categorical variables
Chi-Square test
Only continuous variables
Non dependent relations
Correlations
Clear dependent relations
Regression models
Dependent variable normally distributed
Linear Regression
Dependent variable not normally distributed
GLM
Dependent variable is count data
Poisson GLM
Dependent variable is 0/1 or proportions
Binomial GLM
Multivariate statistics
