Illustrative Transactions and Financial Statements Answers Essay

report potential problems with obsession selective information. 7. respect the advantages and disadvantages of alternative embody images. 8. (Appendix A) Use Microsoft Excel to perform a fixing analysis. 9. (Appendix B) find out the mathematical dealinghip describing the learning phenomenon. Why envision salute? Managers yield findings and need to comp be be and bene pass onwards among alternative actions. Good decision requires good development about be, the better these estimates, the better the decision autobuss go out make (Lanen, 2008).. Key Question What adds value to the theater?Good decisions. You sawing machine in Chapters 3 and 4 that good decisions require good information about be. greet estimates ar important segments in helping managers make decisions that add value to the lodge (Lanen, 2008). study impersonal One Understand the reasons for estimating stock-still and variant be The reasons for estimating unyielding and inconstant appeal s The elemental predilection in woo estimation is to estimate the coitus in the midst of addresss and the inconstants affecting be, the bell drivers. We focus on the relation among make ups and one important variable that affect them act (Lanen, 2008). elemental make up give ear Patterns By now you understand the importance of court demeanour. embody behavior is the key distinction for decision making. embody have a bun in the oven as either fixed or variable (Lanen, 2008). Fixed be ar fixed in append, variable equal vary in entire. On a per- unit basis, fixed salute vary inversely with exercise and variable be stay the same. Are you getting the idea? woo behavior is critical for decision making. The formula that we practice session to estimate costs is similar cost equation agree costs = fixed costs + variable cost per unit number of unitsT c = f + v x With a change in Activity In match Per unit Fixed Cost Fixed Vary variant Vary Fixed What syst ems ar go for to Estimate Cost Behavior? Three general manners utilize to estimate the affinity amidst cost behavior and performance aims that are comm besides employ in drill Engineering estimates, posting analysis & statistical rules (Such as throwback analysis) (Lanen, 2008). Results are likely to differ from method to method. Consequently, its a good idea to use more(prenominal) than one method so that results can 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 establish on measuring and then pricing the work involved in a task. This method based on detailed plans and is frequently used for large projects or new products. This method often omits inefficiencies, such as down eon for unscheduled maintenance, absenteeism and other miscellaneou s random events that affect the entire impregnable (Lanen, 2008). Identify the activities involved Labor Rent Insurance Time Cost Advantages of engineering estimates Details each step required to perform an mathematical process Permits comparison of other centers with similar operations Identifies strengths and weaknesses. Disadvantages of engineering estimates 1. Can be quite expensive to use.Learning Objective Three Estimate costs using mark analysis. measure abbreviation Estimating costs using account analysis involves a review of each account making up the sum of money costs being analyzed and identifying each cost as either fixed or variable, depending on the relation between the cost and some activity. Account analysis relies heavily on personal thinker. This method is often based on last items cost along and is subject to managers focusing on specific issues of the previous period even though these readiness be unusual and infrequent(Lanen, 2008) . pattern Accoun t Analysis ( confront 5. 1) 3C Cost theme utilize Account Analysis Costs for 360 Repair Hours Account Total Variable Cost Fixed Cost Office Rent $3,375 $1,375 $2,000 Utilities 310 coke 210 Administration 3,386 186 3,200 Supplies 2,276 2,176 100 Training 666 316 350 former(a) 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 familiar with company operations and the way costs react to changes in activity levels. Disadvantages of Account Analysis 1. Ma nagers and accountants may be biased. 2.Decisions often have major stinting 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(prenominal) periods of operation or several locations as the basis for estimating cost dealings . We can do this by applying statistical theory, which all toldows for random events to be apart(p) from the underlying relation between costs and activities. A statistical cost analysis analyzes costs indoors the relevant frame using statistics. Do you remember how we defined relevant purge? A relevant array is the range of activity where a cost estimate is valid.The relevant range for cost estimation is usually between the upper and lower limits of by by activity levels for which information is available (Lanen, 2008). Example budget items Costs for 3C ( Exhibit 5. 2) The following information is used throughou t this chapter present we have the smash-up costs data for 3C for the last 15 months. Lets use this data to estimate costs using a statistical analysis. calendar 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 chart Plot of cost and activity levelsDoes it look like a relationship exists between repair-hours and smash costs? We will start with a dismantle chart. A scatter graph is a plot of cost and activity levels. This gives us a visual representation of costs. Does it look like a relationship exists between repair-hours and belt cost? We use eyeball judgment to determine the interfere and hawk of the railroad line. Now we eyeball the scatter graph to determine the intercept and the slope of a line through the data points. Do you remember graphing our thorough cost in Chapter 3? Where the gist 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 give 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 computation 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 compares 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) 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 Difference C. Statistical Cost Estimation Using Regression Analysis Statistical procedure 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 estimate costs. pic Regression AnalysisRegression statistically measures the relationship between tw o variables, activities and costs. Regression techniques are designed to generate a line that best fits a pay off of data points. In addition, backsliding 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 model, that is the hypothesized relation between costs and cost prognosticators (3) know the characteristics of the data being well-tried (4) examine a plot of the data .For 3C, repair-hours are the activities, the in parasitical variable or predictor variable. In regression, the self-employed person variable or predictor variable is identified as the X term. An everywherehead 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 regression equation, Y= a + bX represents the cost equation.Y equals the intercept plus the slope cadences 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 expatiate and theory to computer and statistics course we will focus on the use and get a lineation 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 output. Interpreting Regression pic Interpreting regression output allows us to estimate total overhead costs.The intercept of 6,472 is total fixed costs and the coeffic ient, 12. 52, is the variable cost per repair-hours. Correlation coefficient R measures the unidimensional 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 hearty of the correlation coefficient. The affinity of the variation in the dependent variable (Y) explained by the free-living 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 Multiple R is called the correlation coefficient and measures the elongated relationship between the independent and dependent variables. R Square, the square of the correlation cost efficient, dete rmines 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 Multiple R, the correlation coefficient, of . 91 tells us that a li adjacent 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 part in order to predict the total cost. Lets 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 modify 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 separate. 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 regression data. Implementation Problems Its easy to be over co nfident when interpreting regression output. It all looks so official. But heed 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 model to nonlinear data. Likely to occur near full-capacity. declaration 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 indicate 5. 5. 2. Outliers Problem Outlier moves the regression line.Solution Prepare a s catter-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 presentation 5. 6. 3. Spurious or false relations Problem Using as well many variables in the regression. For example, using direct labor to explain materials costs.Although the friendship is very high, actually both are driven by output. Solution Carefully 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 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. trust 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 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? care must weigh the cost-benefit related to each method (Lanen, 2008). Estimated manufacturing overhead with 520 repair-hours and $3,5 00 parts costs *.The more sophisticated methods yield more accurate 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 a(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 analysis. The analyst must be well schooled in regression in order to determine the mean ing of the output Learning Objective order (Appendix B) Understand the mathematical relationship describing the learning phenomenon. Learning Phenomenon Leaning phenomenon refers to the opinionated 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 ordinal Unit 51. hours (80 percent x 64 hours Impact Causes the unit terms to decrease as production increases. This implies a nonlinear model. Another element that can change the shape of the total cost curve is the persuasion 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 EXERCISE 5-25 A& B riddle 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