Brianna timely filed her 2019 tax return on March 1, 2020. She had a balance due, which she paid on April 15, 2020. She later determined that she had failed to claim an education credit for which she was eligible. The credit would have reduced her tax liability that year. The latest Brianna can file an amended return to correct the originally filed 2019 return and claim the credit is:

In its first year of operations, crane company recognized $31,700 in service revenue, $7,700 of which was on account and still outstanding at year-end. the remaining $24,000 was received in cash from customers. the company incurred operating expenses of $16,600. of these expenses, $12,690 were paid in cash; $3,910 was still owed on account at year-end. in addition, crane prepaid $3,260 for insurance coverage that would not be used until the second year of operations.

The law says your employer is responsible for providing you with a safe and healthy workplace. true or false?

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.