A metal fabrication company is considering entering the global market. It is unsure of what steps to take and is looking for a cost-effective method to enter into the market by partnering with a company who is already doing similar business in the host country. Based on the company's preferences, which mode of entry should the company choose?

An important application of regression analysis in accounting is in the estimation of cost. by collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. consider the following sample of production volumes and total cost data for a manufacturing operation. production volume (units) total cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 compute b 1 and b 0 (to 2 decimals if necessary). b 1 b 0 complete the estimated regression equation (to 2 decimals if necessary). = + x what is the variable cost per unit produced (to 1 decimal)? $ compute the coefficient of determination (to 4 decimals). note: report r 2 between 0 and 1. r 2 = what percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? % the company's production schedule shows 500 units must be produced next month. what is the estimated total cost for this operation (to 2 decimals)? $

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.

In terms of the "great wheel of science", statistics are central to the research process (a) only between the hypothesis phase and the observation phase (b) only between the observation phase and the empirical generalization phase (c) only between the theory phase and the hypothesis phase (d) only between the empirical generalization phase and the theory phase