Illustrative Transactions and Financial Statements Answers Essay Example for Free

Illustrative Transactions and fiscal Statements Answers EssayIdentify potential problems with degeneration entropy. 7. Evaluate the advantages and disadvantages of alternative equal infers. 8. (Appendix A) use up Microsoft Excel to transact a regression out occupancy. 9. (Appendix B) Understand the mathematical family similarityship describing the learning phenomenon. Why Estimate comprises? Managers even up decisions and need to comp atomic number 18 exist and benefits among alternative actions. Good decision requires not bad(predicate) information about be, the unwrap these estimates, the better the decision managers will make (Lanen, two hundred8).. Key Question What adds esteem to the firm?Good decisions. You precept in Chapters 3 and 4 that good decisions require good information about climb. Cost estimates are important elements in helping managers make decisions that add value to the company (Lanen, 2008). acquirement object lens wholeness Unders tand the reasons for estimating obstinate and covariant bells The reasons for estimating dogged and variable courts The basic paper in make up union is to estimate the relation amid courts and the variables affecting appeals, the live drivers. We focus on the relation between costs and one important variable that affect them operation (Lanen, 2008).Basic Cost Behavior Patterns By now you understand the importance of cost behavior. Cost behavior is the key bill for decision making. Costs behave as either obstinate or variable (Lanen, 2008). Fixed costs are frigid in be, variable costs vary in total. On a per- social unit of measurement hind end, fixed costs vary inversely with activity and variable costs stay the same. Are you getting the idea? Cost behavior is critical for decision making. The formula that we call to estimate costs is similar cost equation constitutional costs = fixed costs + variable cost per unit number of unitsT c = f + v x With a transpos e in Activity In nitty-gritty Per building block Fixed Cost Fixed Vary Variable Vary Fixed What Methods are utilise to Estimate Cost Behavior? Three general blesss partd to estimate the transactionhip between cost behavior and activity levels that are commonly used in practice Engineering estimates, forecast analysis Statistical systems (Such as regression analysis) (Lanen, 2008). Results are likely to differ from method to method. Consequently, its a good idea to use to a greater extent than one method so that results nooky be compared. These methods, therefore, should be seen as ways to help management arrive at the best estimates possible.Their weakness and strengths require attention. Learning Objective Two Estimate costs using engineering estimates. Engineering Estimates Cost estimates are based on measuring and then pricing the work involved in a toil. This method based on detailed plans and is frequently used for large projects or new products. This method often omits inefficiencies, such as downtime for unscheduled maintenance, absenteeism and other miscellaneous random events that affect the entire firm (Lanen, 2008). Identify the activities involved boil Rent Insurance Time Cost Advantages of engineering estimates Details each step required to consummate an consummation Permits comparison of other centers with similar operations Identifies strengths and weaknesses. Disadvantages of engineering estimates 1. Can be quite dearly-won to use.Learning Objective Three Estimate costs using account analysis. Account analytic thinking 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 nigh activity. Account analysis relies heavily on personal judgment. This method is often based on last periods cost along and is subject to managers center on specific issues of the previous period even though these might be unusual and infrequent(Lanen, 2008) . simulation Account Analysis (Exhibit 5. 1) 3C Cost affection Using Account Analysis Costs for 360 Repair Hours Account Total Variable Cost Fixed Cost Office Rent $3,375 $1,375 $2,000 Utilities 310 one C 210 Administration 3,386 186 3,200 Supplies 2,276 2,176 100 Training 666 316 350 Other 613 257 356 Total $10,626 $4,410 $6,216 Per Repair Hour $12. 25 ($4,410 divided by 360 repair-hours) 3C Cost Estimation Using Account Analysis (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 acquainted(predicate) with company operat ions and the way costs react to changes in activity levels. Disadvantages of Account Analysis 1. Managers and accountants may be biased. 2.Decisions often have major economic consequences for managers and accountants. Learning Objective Four Estimate costs using statistical analysis. The statistical analysis deals with both random and unusual events is to use several periods of operation or several locations as the basis for estimating cost relations . We can do this by applying statistical theory, which quits for random events to be separated from the underlying relation between costs and activities. A statistical cost analysis analyzes costs within the applicable range using statistics. Do you remember how we defined pertinent range? A relevant range is the range of activity where a cost estimate is valid.The relevant range for cost estimation is commonly between the upper and lower limits of past activity levels for which info is available (Lanen, 2008). Example disk ever yplacehead Costs for 3C ( Exhibit 5. 2) The following information is used throughout this chapter present we have the operating cost costs entropy for 3C for the last 15 months. Lets use this entropy 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. Scattergraph Plot of cost and activity levelsDoes it look like a relationship exists between repair-hours and overhead costs? We will start with a scatter graph. A scatter graph is a secret plan of cost and activity levels. This gives us a visual representation of costs. Does it look like a relationship exists between repair-hours and overhead cost? We use eyeball judgment to checker the interpose and slope of the direct contrast. Now we eyeba ll the scatter graph to delay the intercept and the slope 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 represents fixed cost. What we are saying is the intercept equals fixed costs.The slope of the line represents the variable cost per unit. So we use eyeball judgment to determine fixed cost and variable cost per unit to arrive at total cost for a given level of activity. As you can 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 significantly out of line. B. High-Low Cost Estimation A method to estimate costs based on devil cost observations, usually at the highest and lowest activity level.Although the high-low method allows a c om throw offation of estimates of the fixed and variable costs, it ignores most of the information available to the analyst. 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 net activity F = Total cost at highest activity level V (Highest activity) Or F = Total cost at lowest activity level V (Lowest activity) Lets 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 deflexion C. Statistical Cost Estimation Using Regression Analysis Statistical performance to determine the relationship between variables High-Low Method Uses two data points. Regression analysis Regression is a statistical procedure that uses all the data points to e stimate costs. pic Regression AnalysisRegression statistically measures the relationship between two variables, activities and costs. Regression techniques are designed to generate a line that best fits a set of data points. In addition, regression techniques generate information that helps a manager determine how well the estimated regression equation describes the relations between costs and activities (Lanen, 2008). We recommend that users of regression (1) fully understand the method and its limitations (2) specify the mannikin, that is the hypothesized relation between costs and cost predictors (3) know the characteristics of the data being tested (4) examine a plot of the data .For 3C, repair-hours are the activities, the unconditional variable or predictor variable. In regression, the independent variable or predictor variable is identified 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-hour s, 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 regression 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 leave the description of the computational details and theory to computer and statistics course we will focus on the use and interpretation of regression estimates. We describe the steps required to obtain regression estimates using Microsoft Excel in Appendix A to this chapter. Learning Objective Five Interpret the results of regression create. Interpreting Regression pic Interpreting regression output allows us to estimate total overhead cost s.The intercept of 6,472 is total fixed costs and the coefficient, 12. 52, is the variable cost per repair-hours. Correlation coefficient R measures the linear relationship between variables. The closer 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 R2 The square of the correlational statistics coefficient. The proportion of the chance variable in the dependent variable (Y) explained by the independent 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 totally fixed. The significant level of the t-statistics is called the p-value. Continuing to interpret the regression output, the sevenfold R is called the correlation coefficient and measures the linear relationship between the independent and dependent v ariables. R Square, the square of the correlation 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 fivefold 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 lead to more precise results if 3C uses both repair hours and the cost of parts in order to predict the total cost. Lets look at this example. Predictors X1 Repair-hours X2 Parts Cost 3C Cost entropy 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 squared 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 Objective Six Identify potential problems with re gression data. Implementation tasks Its user-friendly to be over confident when interpreting regression output. It all looks so official. But 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 include outliers and the relationships may be spurious. Lets talk a bit about each. Curvilinear costs Outliers Spurious relations Assumptions 1. Curvilinear costs Problem Attempting to fit a linear sticker to nonlinear data. Likely to keep near full-capacity. Solution Define a more limited 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 leaner cost estimate understates the slope of the cost line in the ranges close capacity. This situation is shown in exhibit 5. 5. 2. Outlie rs Problem Outlier moves the regression line.Solution put a scatter-graph, analyze the graph and eliminate highly unusual observations before 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 significant 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 advertise to explain materials costs.Although the association is very high, actually both are driven by output. Solution conservatively analyze each variable and determine the relationship among all elements before using in the regression. 4. Assumptions Problem If the assumptions in the regression are not satisfied then th e 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 for 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(prenominal) cost estimation method can yield 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 connect to each met hod (Lanen, 2008). Estimated manufacturing overhead with 520 repair-hours and $3,500 parts costs *.The more sophisticated methods yield more exact cost estimates than the simple 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 Mismatched time periods No matter what method is used to estimate costs, the results are only as good as the data used. Collecting appropriate data is complicated by missing data, outliers, allocated and discretionary costs, inflation and mismatched time periods. Learning Objective Eight (Appendix A) Use Microsoft Excel to perform a regression analysis. Appendix A Microsoft as a Tool many an(prenominal) software programs exist to aid in performing regression analysis. In order to use Microsoft Excel, the Analysis Tool Pak must be installed. There are software packages that allow users to easily generate a regression analysi s. 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 learning phenomenon. Learning Phenomenon Leaning phenomenon refers to the systematic relationship between the amount of experience in performing a task and the time required to perform it. The learning phenomenon means that the variable costs tend to decrease per unit as the volume increase. Example Unit Time to Produce Calculation of Time First Unit 100 hours (assumed) Second Unit 80 hours (80 percent x 100 hours Fourth 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 production 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 produce more output per hour. This will impact the total cost curve since it leads to a lower per unit cost, the higher the output. Chapter 5 END COURSE WORK cause 5-25 A B PROBLEM 5-47 -A B REFERENCES Lanen , N. W. , Anderson ,W. Sh. Maher ,W. M. ( 2008). Fundamentals of cost accounting. New York McGraw-Hill Irwin. pic