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Concepts to be included

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Presentation on theme: "Concepts to be included"— Presentation transcript:

1 Concepts to be included
Causality Probabilistic (Non-)linear relationship Deterministic Spurious relationship Dependent variable (causal) hypothesis Independent variable Sign or direction (of a causal relationship) Bivariate Footer text: to modify choose ‘Insert’ (or ‘View’ for office 2003 or earlier) then ‘Header and Footer’ 4/4/2019

2 Bivariate associations
Henk van der Kolk

3 Aim Causality: Time order, Association, Non-spurious relationship.
Bivariate associations between variables with various levels of measurement.

4 A relationship between two variables
Exogenous concept Cause X-variable Independent variable Treatment Endogenous concept Effect / Consequence Y-variable Dependent variable Observation

5 Causality in a graph Positive Dependent variable “SIGN” Negative
This is called the ‘sign’ of a relationship. Independent variable

6 Non linear: parabolic Non linear: quadratic Linear negative Dependent variable Independent variable

7 Probabilistic Deterministic: If … then ‘always’ Probabilistic: If … then ‘relatively more/less often’

8 Probabilistic causality in a graph

9 Why probabilistic only?
Measurement error Parsimoneous models: omitted variables

10 Measurement levels of variables
Dichotomous Gender (male, female) of a person Nominal Country in which the headquarter of a company is located Ordinal Innovative power of a company (low, medium, high) Interval IQ scores of employees Ratio Profits or losses of a company

11 Relating variables Using ‘graphs’ to show causal relationships works fine when using interval - or ratio level variables. How to show the relationship between dichtomous and nominal variables?

12 Probabilistic causality in a table
Two dichotomous variables Independent variable A B Total Dependent variable I x X II

13 Probabilistic causality in a table
Two ordinal variables, or nominal variables (with columns and rows ordered by expectation) Independent variable A B C Total Dependent variable I x X II III

14 This micro lecture Causality: Time order, Association,
Non-spurious relationship. Bivariate associations between independent and dependent variables with various levels of measurement

15 Footer text: to modify choose ‘Insert’ (or ‘View’ for office 2003 or earlier) then ‘Header and Footer’ 4/4/2019


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