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| − | == Welcome to Sustainability Methods! == | + | __NOTITLE__ |
| | + | == Welcome to the ''Sustainability Methods Wiki!'' == |
| | + | The aim of this Wiki is to present and explain fundamental methods, terms and tools relevant to (Sustainability) Science and discuss underlying questions. The Wiki is composed of several sub-wikis: |
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| − | === Day 1 - Intro === | + | {{ContentGrid |
| − | # [[Why statistics matters|Do models and statistics matter?]] Why does it pay to be literate in statistics and R?
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| − | # Getting concepts clear: Generalisation, Sample, and Bias
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| − | #:- See also, [[Misunderstood concepts in statistics|misunderstood concepts]]
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| − | # [[Why statistics matters#A very short history of statistics|History of statistics]]
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| − | === Day 2 - Data formats based on R === | + | {{InfoCard |
| − | # [[Data formats#Continuous data|Continuous vs. categorical, and subsets]]
| + | |heading = [[Courses]] | class = center | |
| − | # [[Data distribution|Normal distribution]]
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| − | # Poisson, binomial, Pareto
| + | <nowiki></nowiki> |
| | + | This section revolves around '''curated selections of Wiki entries (and more)''' as introductions to specific topics. |
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| − | === Day 3 - Simple tests === | + | {{InfoCard |
| − | # [[Simple Tests|Parametric and non-parametric]]
| + | |heading = [[Methods]] | class = center | |
| − | # [[Hypothesis building|Hypothesis testing]]
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| − | # [[Designing studies#P-value|The power of probability]]
| + | <nowiki></nowiki> |
| | + | Methods are at the heart of scientific research. '''Learn about the most important methods in Sustainability Science - and beyond.''' |
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| − | === Day 4 - Correlation and regression ===
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| − | == What are correlation and regressions ==
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| − | Propelled through the general development of science during the Enlightenment, numbers started piling up. With more technological possibilities to measure more and more information, and slow to store this information, people started wondering whether these numbers could lead to something. The increasing numbers had diverse sources, some were from science, such as Astronomy or other branches of natural science. Other prominent sources of numbers were from engineering, and even other from economics, such as double bookkeeping. It was thanks to the tandem efforts of Adrien-Marie Legendre and Carl Friedrich Gauss that mathematics offered with the methods of least squares the first approach to relate one line of data with another. How is one continuous variable related to another? The box of the Panters was opened, and questions started to emerge. Economists were the first who utilised regression analysis at a larger scale, relating all sorts of economical and social indicators with each other, building an ever more complex controlling, management and maybe even understanding of statistical relations. The Gross domestic product -or GDP- became for quite some time kind of a pet variable for many economists, and especially Growth become a core goal of many analysis to inform policy. What people basically did is ask themselves, how one variable is related to another variable. If nutrition of people increases, do they live longer (Yes). If Economies have a higher GDP do they offer more social security (No). Does a higher income lead to more Co2 emissions at a country scale (yes). As these relations started coming in the questions of whether two continuous variables are casually related becoming a nagging thought. With more and more data being available, correlation became a staple of modern statistics. There are some core questions related to the application of correlations and regressions.
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| − | 1) Are relations between two variables positive or negative?
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| − | Relations between two variables can be positive or negative. Being taller leads to a significant increase in body weight. Being smaller leads to an overall lower gross calorie demand. The strength of this relation -what statisticians call the estimate- is an important measure when evaluating correlations and regressions. Is a relation positive or negative, and how strong is the estimate of the relation?
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| − | 2) Does the relation show a significantly strong effect, or is it rather weak? In other words, can the regression explain a lot of variance of your data, or is the results rather weak regarding its explanatory power? Take EXAMPLE
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| − | 3) Relation can explain a lot of variance for some data, and less variance for other parts of the data. Take the percentage of people working in Agriculture within individual countries. At a low income (<5000 Dollar/year) there is a high variance. Half of the population of the Chad work in agriculture, while in Zimbabwe with a even slightly lower income its 10 %. At an income above 15000 Dollar/year, there is hardly any variance in the people that work in agriculture within a country. The proportion is very low. This has reasons, there is probably one or several variables that explain at least partly the high variance within different income segments. Finding such variance that explain partly unexplained variance is a key effort in doing correlation analysis.
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| | + | |heading = [[Skills & Tools]] | class = center | |
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| | + | <nowiki></nowiki> |
| | + | Every type of work can be facilitated through appropriate Skills & Tools. '''Dive in and learn something new!''' |
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| − | == Causal vs non-causal relations == | + | {{InfoCard |
| | + | |heading = [[Normativity of Methods]] | class = center | |
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| | + | <nowiki></nowiki> |
| | + | The choice of methods influences the knowledge we produce. '''Here you can learn more about this relation.''' |
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| − | #:- See also, [[Misunderstood concepts in statistics#Correlation|misunderstood concepts]] | + | == First time visitor? == |
| − | # Are all correlations causal?
| + | '''Please watch this short introduction to the Wiki.''' |
| − | # Is the world linear?
| + | {{#evu:https://www.youtube.com/watch?v=MjlJTjzLg6M |
| − | # Transformation
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| | + | <br/> |
| | + | * Have a look at the '''[[Sustainability_Methods:About|About]] page.''' Here, you will find more information on what the Wiki is all about. It also contains a FAQ section with answers to some general questions concerning the Wiki, and a contact mail in case you would like to provide feedback or ask further questions. |
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| − | === Day 5 - Correlation and regression ===
| + | * Now you can get started! '''Pick a section above''' and choose one or more entries to learn about. <br/> |
| − | # [[Designing studies#P-value|P values]] vs. [[Designing studies#Sample size|sample size]]
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| − | # Residuals
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| − | # Reading correlation plots
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| − | === Day 6 - Designing studies Pt. 1 ===
| + | * If you do not know which methods to start with, have a look at the '''[https://sustainabilitymethods.org/method_recommendation_tool Method Recommendation Tool]'''! |
| − | # How do I compare more than two groups?
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| − | # Designing experiments - degrees of freedom
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| − | # One way and two way
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| − | === Day 7 - Designing studies Pt. 2 ===
| + | * You can also generate a random entry on top of the page or read one of the 5 newest Wiki entries: |
| − | # Balanced vs. unbalanced - Welcome to the Jungle
| + | {{Special:NewestPages/-/5}} |
| − | # [[Designing studies#Block effects|Block effects]]
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| − | # Interaction and reduction
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| − | === Day 8 - Types of experiments ===
| + | __NOTOC__ |
| − | # Are all laboratory experiment really made in labs?
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| − | # Are all field experiment really made in fields?
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| − | # What are natural experiments?
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| − | === Day 9 - Statistics from the Faculty ===
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| − | === Day 10 - Statistics down the road ===
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| − | # Multivariate Statistics
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| − | # AIC
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| − | === Day 11 - The big recap ===
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| − | # Distribution & simple test
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| − | # Correlation and regression
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| − | #:- See also, [[Misunderstood concepts in statistics|misunderstood concepts]]
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| − | # [[Analysis of Variance]]
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| − | === Day 12 - Models ===
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| − | # Are models wrong?
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| − | # Are models causal?
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| − | # Are models useful?
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| − | === Day 13 - Ethics and norms of statistics ===
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| − | # What is informed consent?
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| − | # How does a board of ethics work?
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| − | # How long do you store data?
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| − | View [https://sustainabilitymethods.org/index.php/Special:AllPages All Pages].
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| − | == Admin Tools ==
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| − | * [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Configuration_settings Configuration settings list]
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| − | * [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:FAQ MediaWiki FAQ]
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| − | * [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]
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| − | * [https://www.mediawiki.org/wiki/Special:MyLanguage/Localisation#Translation_resources Localise MediaWiki for your language]
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| − | * [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Combating_spam Learn how to combat spam on your wiki]
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