1) Research design: validity and reliability
Validity = do the results represent what you are trying to measure?
Internal validity = correct conclusions about causal relationship
between variables
External validity = findings of sample generalizable to the population
Treaths to validity:
Omitted variables (leaving out correlated IV that influences DV >
over- or underestimation of strength relationship > control by
intergrating it to model)
Reverse causality (funding success and entrepreneurial
experience)
Sample selection (bias: randomization is not achieved > i.i.d.)
Measurement error (random mistakes data analyst = no problem,
underrepporation of education level = problematic, difficulties in
measuring skill level employees DV = less problematic)
Reliability = extend to which measures are stable, repeatable and
consistent
, 1) Types and distributions of variables
Validity = do the results represent what you are trying to measure?
Internal validity = correct conclusions about causal relationship
between variables
External validity = findings of sample generalizable to the population
Treaths to validity:
Omitted variables (leaving out correlated IV that influences DV >
over- or underestimation of strength relationship > control by
intergrating it to model)
Reverse causality (funding success and entrepreneurial
experience)
Sample selection (bias: randomization is not achieved > i.i.d.)
Measurement error (random mistakes data analyst = no problem,
underrepporation of education level = problematic, difficulties in
measuring skill level employees DV = less problematic)
Reliability = extend to which measures are stable, repeatable and
consistent
, 1) Types and distributions of variables
