Heather owns a two-story building. the building is used 40% for business use and 60% for personal use. during 2019, a fire caused major damage to the building and its contents. heather purchased the building for $800,000 and has taken depreciation of $100,000 on the business portion. at the time of the fire, the building had a fair market value of $900,000. immediately after the fire, the fair market value was $200,000. the insurance recovery on the building was $600,000. the contents of the building were insured for any loss at fair market value. the business assets had an adjusted basis of $220,000 and a fair market value of $175,000. these assets were totally destroyed. the personal use assets had an adjusted basis of $50,000 and a fair market value of $65,000. these assets were also totally destroyed. if heather's agi is $100,000 before considering the effects of the fire, determine her itemized deduction as a result of the fire. also determine heather’s agi.

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.