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Which is a capability of a presentation software program?
calculating mathematical...
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Business, 21.06.2019 21:30
Recently, verizon wireless ran a pricing trial in order to estimate the elasticity of demand for its services. the manager selected three states that were representative of its entire service area and increased prices by 5 percent to customers in those areas. one week later, the number of customers enrolled in verizon's cellular plans declined 4 percent in those states, while enrollments in states where prices were not increased remained flat. the manager used this information to estimate the own-price elasticity of demand and, based on her findings, immediately increased prices in all market areas by 5 percent in an attempt to boost the company's 2016 annual revenues. one year later, the manager was perplexed because verizon's 2016 annual revenues were 10 percent lower than those in 2015"the price increase apparently led to a reduction in the company's revenues. did the manager make an error? yes - the one-week measures show demand is inelastic, so a price increase will decrease revenues. yes - the one-week measures show demand is elastic, so a price increase will reduce revenues. yes - cell phone elasticity is likely much larger in the long-run than the short-run. no - the cell phone market must have changed between 2011 and 2012 for this price increase to lower revenues.
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Business, 21.06.2019 22:50
The winston company estimates that the factory overhead for the following year will be $1,250,000. the company has decided that the basis for applying factory overhead should be machine hours, which is estimated to be 50,000 hours. the total machine hours for the year were 54,300. the actual factory overhead for the year were $1,375,000. determine the over- or underapplied amount for the year.
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Business, 21.06.2019 23:30
Using the exxon data as an example what would be the market capitalization of penny's pickles if each share is selling for $175.35?
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Business, 22.06.2019 02:30
The monthly sales for yazici​ batteries, inc., were as​ follows: month jan feb mar apr may jun jul aug sept oct nov dec sales 19 20 17 12 11 18 16 17 19 22 21 24 this exercise contains only parts b and c. ​b) the forecast for the next month​ (jan) using the naive method​ = nothing sales ​(round your response to a whole​ number). the forecast for the next period​ (jan) using a​ 3-month moving average approach​ = nothing sales ​(round your response to two decimal​ places). the forecast for the next period​ (jan) using a​ 6-month weighted average with weights of 0.10​, 0.10​, 0.10​, 0.20​, 0.20​, and 0.30​, where the heaviest weights are applied to the most recent month​ = nothing sales ​(round your response to one decimal​ place). using exponential smoothing with alpha ​= 0.40 and a september forecast of 21.00​, the forecast for the next period​ (jan) = nothing sales ​(round your response to two decimal​ places). using a method of trend​ projection, the forecast for the next month​ (jan) = nothing sales ​(round your response to two decimal​ places). ​c) the method that can be used for making a forecast for the month of march is ▾ a 3-month moving average a 6-month weighted moving average exponential smoothing the naive method a trend projection .
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