On January 1 of the current year, the records of Khouri Corporation showed the following regarding a truck: Equipment (estimated residual value, $9,000) $ 24,000 Accumulated depreciation (straight-line, three years) 9,000 On December 31 of the current year, the delivery truck was a total loss as the result of an accident. Required: 1. Based on the data given, compute the estimated useful life of the truck. 2. Prepare all journal entries with respect to the truck on December 31 of the current year, assuming there was no insurance coverage on the truck. 3. Assuming Khouri had casualty insurance on the truck and received $8,000 from the insurance company for the accident, determine whether there was a gain or loss for the disposal and what the associated amount was.

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.