The pretax financial income (or loss) figures for Cheyenne Company are as follows.

2012 $147,000
2013 244,000
2014 72,000
2015 (147,000 )
2016 (370,000 )
2017 110,000
2018 93,000

Pretax financial income (or loss) and taxable income (loss) were the same for all years involved. Assume a 40% tax rate for 2012 and 2013 and a 35% tax rate for the remaining years. Prepare the journal entries for the years 2014 to 2018 to record income tax expense and the effects of the net operating loss carrybacks and carryforwards assuming Cheyenne Company uses the carryback provision. All income and losses relate to normal operations.

4. project memo your supervisor has asked you to create a final copy of a memo announcing a special project. open the microsoft® word file ch01 memo from the data files. edit the memo to correct errors in keyboarding, punctuation, spelling, and word usage. submit the edited document to your instructor along with this assignment.to: department supervisorsfrom: tomas perezdate: january 3, 20--subject: playground projectas you now, are offices are close each year on observance of martin luther king, jr. day. this year, the company is organizing a service project for that day. we will be clean up the grove street playground and panting bushes, blubs, and flowers. the company is donating now playground equiptment and park benches. cleanup gear and tools will be provided, and a cook out will conclude the days’ activities. farther information will be provided as the date draws nearer. encourage the employee in you department too participate in this worthwhile effort.

If you were running a company, what are at least two things you could do to improve its productivity.

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)? $