Gibrat's Law of Proportionate Growth says that the probability of growing by a certain percentage over a given period of time is independent of initial asset size. An industry governed by such a law will exhibit a lognormal distribution for firm size. Why do we care?
A. The predictions of Gibrat's Law perfectly match those of the Cournot oligopoly model.
B. In the data, firm size for many mature industries appears to be lognormal distribution is perfectly flat.
C. In the data, firm size is roughly symetrically distributed, and the lognormal distribution is perfectly flat.
D. In the data, smaller/younger firms' sizes appear to be lognormally ditributed.

Which of the following areas provides residents with close access to high-paying jobs and cultural attractions? a. the suburbs b. exurbs c. rural areas d. the city 2b2t

Aprofessional does specialized work that's primarily: degree based. medical or legal. well paying. intellectual and creative

Reliability and validity reliability and validity are two important considerations that must be made with any type of data collection. reliability refers to the ability to consistently produce a given result. in the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways. unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. to illustrate this concept, consider a kitchen scale that would be used to measure the weight of cereal that you eat in the morning. if the scale is not properly calibrated, it may consistently under- or overestimate the amount of cereal that’s being measured. while the scale is highly reliable in producing consistent results (e.g., the same amount of cereal poured onto the scale produces the same reading each time), those results are incorrect. this is where validity comes into play. validity refers to the extent to which a given instrument or tool accurately measures what it’s supposed to measure. while any valid measure is by necessity reliable, the reverse is not necessarily true. researchers strive to use instruments that are both highly reliable and valid.