Robin Mackey is a business major at Southern Missouri University. Robin is struggling with an accounting homework assignment to prepare an income statement for Wambaugh Inc., an imaginary firm. Robin has decided that the following should be included in this income statement:Costs of Goods SoldIncome Taxes PayableAccounts ReceivableIncome ExpenseEarnings per ShareLoss of Discontinued Operations (net of taxes)Net salesPossible loss from LawsuitAccounts PayableDividends (declared by the Board of Directors)Gain on Sale of EquipmentSalaries PayableSelling and Administrative ExpensesStock Dividends DistributableHelp Robin complete her homework assignment by answering the following questions:1. Which of the items listed should be included in Wambaugh Inc.’s income statement?2. In what order should these items appear in the income statement?3. Where will the remaining items appear in the financial statements? Will any of the amounts not be included in the actual financial statements? If so, explain.

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.