Tracie, working at a research facility in washingtond. c., needs to communicate with juan, who is in mexico city, about a project they are working on. although juan has perfect command of english, they are still facing a(n) barrier to communication.

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.

The state in which the manufacturing company you work for is located regulates the presence of a particular substance in the environment to concentrations ≤ x. recently-released, reliable research endorsed by the responsible federal agency conclusively demonstrates that the substance poses no risks at concentrations up to 5x. your company has asked you to consider designing a new process with a waste discharge stream containing up to 2x of the substance. based on the stated conditions, describe this possible.

Investors who put their own money into a startup are known as a. mannequins b. obligators c. angels d. borrowers