Difference between revisions of "Bachelor Statistics Lecture"

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Bachelor Statistics Lecture
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== Overview of the lecture structure ==
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This course provides an introduction to statistics on a bachelor level.
  
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Day 1 - Why statistics?
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=== Day 1 - [[Why_statistics_matters|Why statistics matters]] ===
 
<br>
 
<br>
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A very short history of statistics.
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[[Why_statistics_matters#The_Power_of_Statistics|The Power of Statistics]]
 
<br>
 
<br>
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The Power of statistics
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[[Why_statistics_matters#Statistics_as_a_part_of_science|Statistics as a part of science]]
 
<br>
 
<br>
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The scientific landscape and statistics
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[[Why statistics matters#A very short history of statistics|A very short history of statistics]]
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<br>
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[[Why_statistics_matters#Key_concepts_of_statistics|Key concepts of statistics]]
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=== Day 2 - [[Data formats]] and [[Data_formats#Descriptive_statistics|descriptive stats]] ===
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<br>
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[[Data_formats#Continuous_data data|Continuous data]]
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<br>
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[[Data_formats#Ordinal_data|Ordinal data]]
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<br>
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[[Data_formats#Descriptive_statistics|Descriptive statistics]]
  
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Day 2 - Data formats and descriptive stats
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=== Day 3 - [[Data_distribution|Data distribution and Probability]] ===
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Continuous data
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<br>
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Data constructs and indices
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[[Data_distribution#The_normal_distribution|Normal distribution]]
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Descriptive statistics
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<br>
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[[Data_distribution#Non-normal distributions|Non-normal distributions]]
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<br>
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[[Data_distribution#A matter of probability|A matter of Probability]]
  
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Day 3 - Distribution
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=== Day 4 - [[Hypothesis_building|Hypothesis building and simple tests]] ===
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Normal distribution
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<br>
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Other distributions
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[[Hypothesis_building|Hypothesis testing]]
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Probabilities
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<br>
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[[Hypothesis_building#Validity |Validity]]
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<br>
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[[Hypothesis_building#Simple tests |Simple tests]]
  
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Day 4 - Simple tests
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=== Day 5 - [[Correlations|Correlations]] ===
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Normal distribution
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<br>
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Other distributions
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[[Correlations|Correlations on a shoestring]]
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Probability
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<br>
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[[Correlations#Reading_correlation_plots|Reading correlation plots]]
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<br>
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[[Correlations#Correlative_relations|Correlative relations]]
  
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Day 5 - Correlation
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=== Day 6 - Regression ===
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Significance, residuals and sum of squares
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<br>
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Reliability and validity
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[[Causality|Causality]]
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Transformations
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<br>
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[[Causality#Residuals|Residuals]]
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<br>
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[[Causality#Significance_in_regressions|Significance in regressions]]
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<br>
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[[Causality#Is_the_world_linear.3F|Is the world linear?]]
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<br>
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[[Causality#Prediction|Prediction]]
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<br>
  
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Day 6 - Regression
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=== Day 7 - Design 1 - Simple Anova OR the lab experiment ===
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Causality
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<br>
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Prediction
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[[Experiments#The_laboratory_experiment|The laboratory experiment]]
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XX
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<br>
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[[Experiments#How_do_I_compare_more_than_two_groups_.3F|How do I compare more than two groups?]]
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<br>
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[[Designing_studies|Designing studies]]
  
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Day 7 - Design 1 - Simple Anaya OR the lab experiment
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=== Day 8 - Design 2 - [[Field experiments|Field experiments]] ===
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Designing an experiment
 
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Controlled variables
 
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Explained variance
 
  
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Day 8 - Design 2 - Field experiments
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=== Day 9 - [[Case studies and Natural experiments|Case studies and natural experiments]] ===
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Interaction effects
 
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Replicates
 
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Random factors
 
  
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Day 9 - Case studies and natural experiments
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=== Day 10 - Bias ===
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Number of variables vs number of samples
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<br>
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Transferability of single cases
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[[Bias in statistics]]
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Meta-Analysis
 
  
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Day 10 - Bias
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=== Day 11 - [[Statistics and mixed methods|Statistics and mixed methods]] ===
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Bias associated to sampling
 
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Bias within analysis
 
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Bias related to interpretation of data and analysis
 
  
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Day 11 - Limits of statistics
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=== Day 12 - [[A word on ethics|A word on ethics]] ===
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Mixed methods
 
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Statistics and disciplines
 
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A qualitative methods view on statistics
 
  
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Day 12 - A word on ethics
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=== Day 13 - [https://sustainabilitymethods.org/index.php/The_big_recap The Big recap] ===
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Confusion through statistics
 
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Statistics serving immoral goals
 
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How statistics can fuel anger
 
  
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Day 13 - The Big recap
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----
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What did we learn?
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[[Category: Courses]]
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Why does it matter?
 
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How to go on?
 

Latest revision as of 13:21, 11 January 2021

Overview of the lecture structure

This course provides an introduction to statistics on a bachelor level.

Day 1 - Why statistics matters


The Power of Statistics
Statistics as a part of science
A very short history of statistics
Key concepts of statistics

Day 2 - Data formats and descriptive stats


Continuous data
Ordinal data
Descriptive statistics

Day 3 - Data distribution and Probability


Normal distribution
Non-normal distributions
A matter of Probability

Day 4 - Hypothesis building and simple tests


Hypothesis testing
Validity
Simple tests

Day 5 - Correlations


Correlations on a shoestring
Reading correlation plots
Correlative relations

Day 6 - Regression


Causality
Residuals
Significance in regressions
Is the world linear?
Prediction

Day 7 - Design 1 - Simple Anova OR the lab experiment


The laboratory experiment
How do I compare more than two groups?
Designing studies

Day 8 - Design 2 - Field experiments

Day 9 - Case studies and natural experiments

Day 10 - Bias


Bias in statistics

Day 11 - Statistics and mixed methods

Day 12 - A word on ethics

Day 13 - The Big recap

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