'Accounting for Operational Activities: Illustrative Transactions and Financial Statements Answers\r'

'CHAPTER FIVE: COST ESTIMATION fundament When managers contri plainlye decisions they need to comp atomic number 18 the woo (and bene rivals) among secondary actions. In this chapter, we discuss how to consider the be required for decision qualification (Lanen, two hundred8). acquisition intents: According to Lanen (cc8), after complemental Chapter 5 you should: 1. Understand the reasons for estimating amend and multivariate comprise. 2. Estimate hail engage engine room assessments. 3. Estimate woo victimization depend compend. 4. Estimate be using statistical analysis. 5. Interpret the results of obsession sidetrack. 6.Identify strength problems with retroflexion information. 7. Evaluate the advantages and disadvantages of alternative comprise labels. 8. (Appendix A) white plague Microsoft Excel to execute a lapse analysis. 9. (Appendix B) Understand the mathematical notificationship describing the tuition phenomenon. Why Estimate tolls? Manage rs make decisions and need to comp atomic number 18 be and benefits among alternative actions. Good decision requires computable information intimately be, the better these sees, the better the decision managers will make (Lanen, cc8).. Key interrogatory What attention deficit dis sites comfort to the unanimous?\r\nRead this fiscal StatementsGood decisions. You saw in Chapters 3 and 4 that good decisions require good information about represents. address augurs atomic number 18 of import parts in processing managers make decisions that add value to the attach to (Lanen, 2008). Learning object One: Understand the reasons for estimating icy and changeable appeal The reasons for estimating restore and versatile approach The basic idea in follow regard is to enter the relation amid be and the multivariates makeing be, the address drivers. We rivet on the relation betwixt equal and building blocky important inconsistent quantity that affect them: activeness (Lanen, 2008).Basic live bearing Patterns By now you understand the importance of salute demeanor. Cost appearance is the key tuberosity for decision making. Costs be take as either firm or covariant (Lanen, 2008). frozen be atomic number 18 firm in aggregate, variable costs divert in total. On a per- unit of measurement footing, fixed costs vary inversely with body process and variable costs stay the same. be you getting the idea? Cost appearance is critical for decision making. The formula that we drug abuse to estimate costs is similar cost equation: hit costs = fixed costs + {variable cost per unit} number of unitsT c = f + {v} x |With a change in Activity |In organic |Per building block | |Fixed Cost |Fixed | falsify | |Variable |Vary |Fixed |What Methods ar apply to Estimate Cost Behavior? Three general orders used to estimate the dealingship between cost behavior and exercise directs that are comm and used in practice: Engineerin g estimates, method of casting analysis & statistical methods (Such as retrogression analysis) (Lanen, 2008). Results are likely to disagree from method to method. Consequently, it’s a good idea to use more than(prenominal) than ane method so that results open fire be compared. These methods, therefore, should be seen as ways to help management grow at the trounce(p) estimates possible.Their weakness and strengths require attention. Learning object glass Two: Estimate costs using design estimates. Engineering Estimates Cost estimates are based on measuring and then pricing the work involved in a assign. This method based on detailed plans and is frequently used for heroic projects or new products. This method a good deal omits inefficiencies, such as down epoch for unscheduled maintenance, absenteeism and opposite miscellaneous ergodic events that affect the built-in firm (Lanen, 2008). Identify the activities involved drive |Rent |Insurance |Time |Co st | Advantages of engineering estimates |Details each mistreat required to perform an operation |Permits analogy of other centers with similar operations | |Identifies strengths and weaknesses. | | Disadvantages of engineering estimates 1. nooky be quite high-ticket(prenominal) to use.\r\nRead also Recording general Fund direct Budget and Operating TransactionsLearning bearing Three: Estimate costs using account analysis. bankers bill compendium Estimating costs using account analysis involves a review of each account making up the total costs being analyzed and identifying each cost as either fixed or variable, depending on the relation between the cost and some bodily process. nib analysis relies to a great extent on personal judgment. This method is very much based on last menses’s cost along and is equal to(p) to managers counsellinging on specific issues of the prior period even though these office be unusual and infrequent(Lanen, 2008) .Example: disti nguish compend ( establish 5. 1) |3C Cost thought Using Account abridgment | |Costs for 360 Repair Hours | |Account | agree |Variable Cost |Fixed Cost | |Office Rent $3,375 |$1,375 |$2,000 | |Utilities |310 | ascorbic acid |210 | |Administration |3,386 |186 |3,200 | |Supplies |2,276 |2,176 |100 | |Training |666 |316 |350 | | early(a) |613 |257 |356 | |Total |$10,626 |$4,410 |$6,216 | |Per Repair Hour |$12. 25 ($4,410 divided by 360 compensate-hours) | 3C Cost musical theme Using Account compendium (Costs at 360 Repair-Hours. A unit is a repair- hour) Total costs = fixed costs + {variable cost per unit} number of unitsT c = f + {v} x |$10,626 = $6,216 + $12. 25 (360) |$10,626 = $6,216 + $$4,410 | Costs at 520 Repair-Hours Total costs = fixed costs + {variable cost per unit} number of units |Tc = $6,216 + {$12. 25} 520 |Total costs = $6,216 + $ $6,370 |$12,586 = $6,216 + $ $6,370 | Advantage of Account Analysis 1. Managers and accountants are familiar with comp whatever operati ons and the way costs fight back to changes in activity levels. Disadvantages of Account Analysis 1. Managers and accountants may be biased. 2.Decisions often restrain major economic consequences for managers and accountants. Learning object glass Four: Estimate costs using statistical analysis. The statistical analysis deals with twain random and unusual events is to use several(prenominal) periods of operation or several locations as the basis for estimating cost traffic . We locoweed do this by applying statistical possibility, which every last(predicate)ows for random events to be separated from the underlying relation between costs and activities. A statistical cost analysis analyzes costs at bottom the relevant regulate using statistics. Do you remember how we defined relevant run away? A relevant range is the range of activity where a cost estimate is valid.The relevant range for cost estimation is usually between the upper and displace limits of past activity leve ls for which selective information is purchasable (Lanen, 2008). Example: bash Costs for 3C ( Exhibit 5. 2) The following information is used throughout this chapter: Here we have the disk everywherehead costs information for 3C for the last 15 months. let’s use this data to estimate costs using a statistical analysis. | month |Overhead Costs |Repair-Hours |Month |Overhead Costs |Repair-Hours | |1 |$9,891 |248 |8 |$10,345 |344 | |2 $9,244 |248 |9 |$11,217 |448 | |3 |$13,200 |480 |10 |$13,269 |544 | |4 |$10,555 |284 |11 |$10,830 |340 | |5 |$9,054 |200 |12 |$12,607 |412 | |6 |$10,662 |380 |13 |$10,871 |384 | |7 |$12,883 |568 |14 |$12,816 |404 | | | | |15 |$8,464 |212 | A. Scatter represent Plot of cost and activity levelsDoes it estimate like a blood bes between repair-hours and command command smash costs? We will start with a break up represent. A scatter graph is a plot of cost and activity levels. This gives us a visual representation of costs. Does it look lik e a relationship exists between repair-hours and overhead cost? We use â€Å" look judgment” to narrow down the end and raftt of the describe. Now we â€Å"globe” the scatter graph to moderate the intercept and the slant of a line through the data points. Do you remember graphing our total cost in Chapter 3? Where the total cost line intercepts the horizontal or Y axis of rotation represents fixed cost. What we are saying is the intercept equals fixed costs.\r\nAlso read reliable Liabilities and Payroll AccountingThe slope of the line represents the variable cost per unit. So we use â€Å"eyeball judgment” to work fixed cost and variable cost per unit to arrive at total cost for a given level of activity. As you potful imagine, preparing an estimate on the basis of a scatter graph is subject to a high level of error. Consequently, scatter graphs are usually not used as the sole basis for cost estimates but to illustrate the relations between costs and activity and to point out any past data items that might be materially out of line. B. High-Low Cost union A method to estimate costs based on two cost observations, usually at the highest and low activity level.Although the high-low method allows a computation of estimates of the fixed and variable costs, it ignores most of the information on tap(predicate) to the psychoanalyst. The high-low method uses two data points to estimate costs (Lanen, 2008). Another approach: Equations V = Cost at highest activity †Cost at lowest activity Highest activity †Lowest activity F = Total cost at highest activity level †V (Highest activity) Or F = Total cost at lowest activity level †V (Lowest activity) Let’s put the numbers in the equations | | | |V = $12,883 †$9,054 |V = $10. 0/RH | |568 †200 | | F = Total cost at highest activity level †V (Highest activity) F = $12,883 †$10. 40 (568), F= $6,976 Or F = Total cost at lowest activity level †V (Lowest activity) F = $9,054 †$10. 40 (200) Rounding Difference C. Statistical Cost idea Using reversal Analysis Statistical procedure to determine the relationship between variables High-Low Method: Uses two data points. relapsing analysis relapse is a statistical procedure that uses all the data points to estimate costs. [pic] Regression AnalysisRegression statistically measures the relationship between two variables, activities and costs. Regression techniques are designed to grant a line that better fits a go down of data points. In addition, statistical reverting techniques generate information that helps a manager determine how well the estimated obsession equation describes the relations between costs and activities (Lanen, 2008). We recommend that users of turnabout (1) fully understand the method and its limitations (2) denominate the model, that is the hypothesized relation between costs and cost predictors (3) drive in the characteristics of the data being tried (4) examine a plot of the data .For 3C, repair-hours are the activities, the in dependant variable or predictor variable. In relapsing, the breakaway variable or predictor variable is place as the X term. An overhead cost is the dependent variable or Y term. What we are saying is; overhead costs are dependent on repair-hours, or predicted by repair-hours. The Regression Equation |Y = a + bX |Y = Intercept + (Slope) X |OH = Fixed costs + (V) Repair-hours | You already know that an estimate for the costs at any given activity level can be computed using the equation TC = F + VX. The lapsing equation, Y= a + bX represents the cost equation.Y equals the intercept plus the slope times the number of units. When estimating overhead costs for 3C, total overhead costs equals fixed costs plus the variable cost per unit of repair-hours times the number of repair-hours. We surrender the description of the computational details and theory to computer and statistics course; we w ill focus on the use and examineation of regression estimates. We describe the steps required to see regression estimates using Microsoft Excel in Appendix A to this chapter. Learning mark Five: Interpret the results of regression sidetrack. rendition Regression [pic] Interpreting regression output allows us to estimate total overhead costs.The intercept of 6,472 is total fixed costs and the coefficient, 12. 52, is the variable cost per repair-hours. Correlation coefficient â€Å"R” measures the additive relationship between variables. The impending R is to 1. 0 the closer the points are to the regression line. The closer R is to zero, the poorer the regression line (Lanen, 2008). Coefficient of determination â€Å"R2” The square of the correlativity coefficient. The proportion of the variation in the dependent variable (Y) formulateed by the self-directed variable(s)(X). T-Statistic The t-statistic is the value of the estimated coefficient, b, divided by its standard error. Generally, if it is over 2, then it is considered significant.If significant, the cost is NOT tout ensemble fixed. The significant level of the t-statistics is called the p-value. Continuing to interpret the regression output, the sextuplex R is called the correlativityal statistics coefficient coefficient and measures the linear relationship between the freelance and dependent variables. R Square, the square of the correlation coefficient cost efficient, determines and identifies the proportion of the variation in the dependent variable, in this case, overhead costs, that is explained by the independent variable, in this case, repair-hours. The quaternate R, the correlation coefficient, of . 91 tells us that a linear relationship does exist between repair-hours and overhead costs.The R Square, or coefficient of determination, tells us that 82. 8% of the changes in overhead costs can be explained by changes in repair-hours. Can you use this regression output to estimate overhead costs for 3C at 520 repair-hours? Multiple Regressions Multiple regressions are used when more than one predictor (x) is needed to adequately predict the value (Lanen, 2008). For example, it might asterisk to more precise results if 3C uses twain repair hours and the cost of separate in order to predict the total cost. Let’s look at this example. |Predictors: |X1: Repair-hours |X2: Parts Cost | 3C Cost Information | |Month |Overhead Costs |Repair-Hours ( X1) |Parts ( X2) | |1 |$9,891 |248 |$1,065 | |2 |$9,244 |248 |$1,452 | |3 |$13,200 |480 |$3,500 | |4 |$10,555 |284 |$1,568 | |5 |$9,054 |200 |$1,544 | |6 |$10,662 |380 |$1,222 | |7 |$12,883 |568 |$2,986 | |8 |$10,345 |344 |$1,841 | |9 |$11,217 |448 |$1,654 | |10 |$13,269 |544 |$2,100 | |11 |$10,830 |340 |$1,245 | |12 |$12,607 |412 |$2,700 | |13 |$10,871 |384 |$2,200 | |14 |$12,816 |404 |$3,110 | |15 |$8,464 |212 |$ 752 | In multiple regressions, the Adjusted R Square is the correlation coefficient squar ed and adjusted for the number of independent variables used to make the estimate. Reading this output tells us that 89% of the changes in overhead costs can be explained by changes in repair-hours and the cost of parts. Remember 82. % of the changes in overhead costs were explained when one independent variable, repair-hours, was used to estimate the costs. Can you use this regression output to estimate overhead costs for 520 repair-hours and $3,500 cost of parts? Learning object lens Six: Identify potential problems with regression data. Implementation jobs It’s wakeful to be over confident when interpretation regression output. It all looks so official. nevertheless beware of some potential problems with regression data. We already discussed in earlier chapters that costs are curvilinear and cost estimations are only valid within the relevant range. Data may also allow outliers and the relationships may be spurious. Let’s talk a bit about each. Curvilinear cos ts |Outliers | specious relations |Assumptions | 1. Curvilinear costs Problem: Attempting to fit a linear model to nonlinear data. Likely to occur near full-capacity. solving: Define a more circumstance(a) relevant range (example: from 25 †75% capacity) or design a nonlinear model. If the cost function is curvilinear, then a linear model contains weaknesses. This generally occurs when the firm is at or near capacity. The anorectic cost estimate understates the slope of the cost line in the ranges close capacity. This postal service is shown in exhibit 5. 5. 2. Outliers Problem: Outlier moves the regression line. termination: Prepare a scatter-graph, analyze the graph and eliminate highly unusual observations in advance running the regression. Because regression calculates the line that best fits the data points, observations that lie a significant distance away from the line could have an overwhelming effect on the regression estimate. Here we see the effect of one signif icant outlier. The computed regression line is a substantial distance from most of the points. The outlier moves the regression line. Please refer exhibit 5. 6. 3. Spurious or false relations Problem: Using too many variables in the regression. For example, using direct labor to explain materials costs.Although the association is very high, actually both are driven by output. rootage: Carefully analyze each variable and determine the relationship among all elements forrader using in the regression. 4. Assumptions Problem: If the assumptions in the regression are not snug then the regression is not reliable. Solution: No clear solution. Limit time to help assure costs behavior remains constant, yet this causes the model to be weaker due to less data. Learning Objective Seven: Evaluate the advantages and disadvantages of alternative cost estimation methods. Statistical Cost Estimation Advantages 1. Reliance on historical data is relatively inexpensive. 2.Computational tools allow f or more data to be used than for non-statistical methods. Disadvantages 1. Reliance on historical data may be the only readily available, cost-effective basis for estimating costs. 2. Analysts must be alert to cost-activity changes. Choosing an Estimation Method Each cost estimation method can collapse a different estimate of the costs that are likely to result from a particular management decision. This underscores the advantage of using more than one method to arrive at a final estimate. Which method is the best? Management must weigh the cost-benefit related to to each method (Lanen, 2008). Estimated manufacturing overhead with 520 repair-hours and $3,500 parts costs *.The more sophisticated methods yield more accurate cost estimates than the wide methods. |Account Analysis = $12,586 |High-Low = $12,384 |Regression= $12,982 |Multiple Regression= $13,588* | Data Problems Missing data Outliers Allocated and discretionary costs Inflation irreconcilable time periods No matter wha t method is used to estimate costs, the results are only as good as the data used. Collecting appropriate data is intricate by missing data, outliers, allocated and discretionary costs, rising prices and mismatched time periods. Learning Objective Eight: (Appendix A) Use Microsoft Excel to perform a regression analysis. Appendix A: Microsoft as a ToolMany software programs exist to aid in performing regression analysis. In order to use Microsoft Excel, the Analysis Tool Pak must be installed. in that location are software packages that allow users to easy generate a regression analysis. The analyst must be well schooled in regression in order to determine the meaning of the output! Learning Objective Nine: (Appendix B) Understand the mathematical relationship describing the accomplishment phenomenon. Learning Phenomenon Leaning phenomenon refers to the arrogant relationship between the amount of engender in performing a task and the time required to perform it. The learning p henomenon means that the variable costs tilt to decrease per unit as the gaudiness increase. Example: | |whole |Time to nurture |Calculation of Time | |First Unit |100 hours |(assumed) | |Second Unit |80 hours |(80 percent x 100 hours | |quartern Unit |64 hours |(80 percent x 80 hours | |Eighth Unit |51. hours |(80 percent x 64 hours | |Impact: Causes the unit price to decrease as take increases. This implies a nonlinear model. | Another element that can change the shape of the total cost curve is the notion of a learning phenomenon. As workers become more skilled they are able to establish more output per hour. This will bear upon the total cost curve since it leads to a lower per unit cost, the higher the output. Chapter 5: END!! COURSE WORK figure out 5-25 †A& B fuss 5-47 -A& B REFERENCES Lanen , N. W. , Anderson ,W. Sh. & Maher ,W. M. ( 2008). rudiments of cost accounting. New York : McGraw-Hill Irwin. [pic]\r\n'