Difference between revisions of "Bachelor Statistics Lecture"

From Sustainability Methods
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=== Day 10 - Bias ===
 
=== Day 10 - Bias ===
 
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[[Bias | Groundwork]]
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[[Bias |Bias]]
 
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[https://sustainabilitymethods.org/index.php/Bias#Bias_in_analyzing_data Different biases]
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[https://sustainabilitymethods.org/index.php/Bias#Bias_in_analyzing_data Bias in analyzing data]
 
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[https://sustainabilitymethods.org/index.php/Bias#A_world_beyond_Bias.3F How to deal with biases?]
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[https://sustainabilitymethods.org/index.php/Bias#A_world_beyond_Bias.3F A world beyond bias?]
  
 
=== Day 11 - [[Statistics and mixed methods|Statistics and mixed methods]] ===
 
=== Day 11 - [[Statistics and mixed methods|Statistics and mixed methods]] ===

Revision as of 15:18, 29 July 2020

Overview of the lecture structure

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
Bias in analyzing data
A world beyond bias?

Day 11 - Statistics and mixed methods

Day 12 - A word on ethics

Day 13 - The Big recap