Both employers and colleges often have a place for you to include your interests on their
a) application
b) survey
c) wish list
d) evaluation

Selected data for stick’s design are given as of december 31, year 1 and year 2 (rounded to the nearest hundredth). year 2 year 1 net credit sales $25,000 $30,000 cost of goods sold 16,000 18,000 net income 2,000 2,800 cash 5,000 900 accounts receivable 3,000 2,000 inventory 2,000 3,600 current liabilities 6,000 5,000 compute the following: 1. current ratio for year 2 2. acid-test ratio for year 2 3. accounts receivable turnover for year 2 4. average collection period for year 2 5. inventory turnover for year 2

Suppose a holiday inn hotel has annual fixed costs applicable to its rooms of $1.2 million for its 300-room hotel, average daily room rents of $50, and average variable costs of $10 for each room rented. it operates 365 days per year. the amount of operating income on rooms, assuming an occupancy* rate of 80% for the year, that will be generated for the entire year is *occupancy = % of rooms rented

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.