Variable
Variable: Observable characteristics that have more than one value
Examples of variables and their values: Budget: dollars / age: years / work effort: overtime in hours
Theory
Theory: Tentative causal explanations behind the relationships of variables.
Hypothesis
Hypothesis: Theory-based statement that specifies the relationship between two variables in a empirically testable way.
Positive Relationship
Higher … causes higher … (positive relationship)
Negative Relationship
Higher … causes lower … (negative relationship)
Covariation
Covariation: a change in one variable corresponds with a
change in another (hence: co-vary)
Causation
Causation: logical, plausible connection between variables
Example: In areas with greater populations of storks, we can count more babies per family. Does this mean storks cause babies?
Time series
Time series
Variation across time
Example: explaining variation in employees’ work motivation over a period of 10 years
cross-sectional
Cross-sectional
Variation among units
Example: explaining variation in work motivation among employees at a certain point in time
Four Causal Hurdles 1&2
Building Theory
- Is there a credible causal mechanism that connects X to Y?
- Could Y cause X?
Four Causal Hurdles 3&4
Testing Theory
- Is there covariation between X and Y?
- Is there some confounding variable Z that could affect Y or even be related to both X and Y.
Scientific Process
- Causal Theory 2. Hypothesis 3. Empirical Test 4. Evaluation of Hypothesis 5. Evaluation of Causal theory 6. Scientific Knowledge
statistical significance
refers to the probability of being wrong about65 stating that a relationship exist s when in fact it doesn’t.