Difference between revisions of "An initial path towards statistical analysis"

From Sustainability Methods
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<div id="Univariate statistics">Univariate statistics</div>
 
<div id="Univariate statistics">Univariate statistics</div>
[[Categorical and continuous data|Data_formats#Data_formats_in_statistics]]<br>
+
[[Data_formats#Data_formats_in_statistics|Categorical and continuous data|]]<br>
 
[[At least one categorical independent variable|
 
[[At least one categorical independent variable|
  
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       More than 2 groups
 
       More than 2 groups
[[Analysis of Variance|https://sustainabilitymethods.org/index.php/Experiments#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 20:38, 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|
[[At least one categorical independent variable|


     More than 2 groups

[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