Difference between revisions of "Bachelor Statistics Lecture"

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[[Data_distribution#The_normal_distribution|Normal distribution]]
 
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[[Data_distribution#Non-normal distributions|Other distributions]]
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[[Data_distribution#Non-normal distributions|Non-normal distributions]]
 
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[[Data_distribution#A matter of probability|Probability]]
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[[Data_distribution#A matter of probability|A matter of Probability]]
  
 
=== Day 4 - [[Hypothesis_building|Hypothesis building and simple tests]] ===
 
=== Day 4 - [[Hypothesis_building|Hypothesis building and simple tests]] ===

Revision as of 08:30, 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
Confidence, uncertainty and reliability
Simple tests - a primer

Day 5 - Correlations


Correlations on a shoestring
Reading correlation plots
Correlative relations

Day 6 - Regression


Causality
Residuals
Significance in regressions
Is the world linear?
Interpolation and extrapolation

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


The laboratory experiment
How do I compare more than two groups?
How to design a study

Day 8 - Design 2 - Field experiments

Day 9 - Case studies and natural experiments

Day 10 - Bias


Groundwork
Different biases
How to deal with biases?

Day 11 - Statistics and mixed methods

Day 12 - A word on ethics

Day 13 - The Big recap