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1 . Analyze your findings given the question you were asked ( which method should be used ) : some questions you may want to

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1. Analyze your findings given the question you were asked (which method should be used): some questions you may want to answer: is receivable aging the right choice for the company given the historical data? Should all the years be included in the analysis? Should you use mean / median to calculate the percentages? Are there any extreme observations that should not be included in the analysis? Do the number of customers matter in a given year? Does the dollar amount of receivables vary significantly and what should you conclude given these differences?
2. Based on your recommendation, calculate the amount of bad debt expense you should report for 2018. Assume beginning balance of Allowance for Uncollectible Accounts is zero in 2018(Provide the analysis of the credit sales or outstanding receivables in each aging category for 2018 that led you to this number in the table above)
3. Your recommendations and the reasoning behind them should you use percent of credit sales or aging of receivables? (Some questions you may want to consider are: is the aging method the right choice for the company given the historical data? Should all the years be included in the analysis? Should you use mean or median to calculate the percentages? Are there any extreme observations that should not be included in the analysis? Do the number of customers matter in a given year? Does the balance of total receivables vary significantly and what you conclude given these differences?)
4. Anything else you would like to share with your CFO (can you think of different data you might be able to use to get a better sense of the write-offs)?\table[[Year,\table[[Total Outstanding],[Receivables]],\table[[Percent of sales on],[account written off]],Percent of outstanding receivables written off by receivale age group],[,,,0-30,31-60,61-90,over 90],[2013,\table[[$],[33,584,855]],1.65%,0.00%,1.92%,3.26%,6.73%],[2014,\table[[$],[37,040,513]],3.37%,0.02%,0.00%,5.31%,14.86%],[2015,\table[[$],[34,048,875]],3.11%,0.02%,3.17%,4.67%,13.15%],[2016,\table[[$],[40,884,402]],1.57%,0.00%,0.00%,4.38%,5.95%],[2017,\table[[$],[40,902,344]],2.03%,0.01%,2.58%,4.30%,6.11%],[2018(predicted),\table[[$],[40,857,493]],2.34%,0.01%,1.53%,4.39%,9.36%]]
Analyze your findings given the question you were asked (which method should be used): some questions you may want to answer: is receivable aging the right choice for the company given the historical data? Should all the years be included in the analysis? Should you use mean / median to calculate the percentages? Are there any extreme observations that should not be included in the analysis? Do the number of customers matter in a given year? Does the dollar amount of receivables vary significantly and what should you conclude given these differences?
Based on your recommendation, calculate the amount of bad debt expense you should report for 2018. Assume beginning balance of Allowance for Uncollectible Accounts is zero in 2018(Provide the analysis of the credit sales or outstanding receivables in each aging category for 2018 that led you to this number in the table above)
Your recommendations and the reasoning behind them - should you use percent of credit sales or aging of receivables? (Some questions you may want to consider are: is the aging method the right choice for the company given the historical data? Should all the years be included in the analysis? Should you use mean or median to calculate the percentages? Are there any extreme observations that should not be included in the analysis? Do the number of customers matter in a given year? Does the balance of total receivables vary significantly and what you conclude given these differences?)
Anything else you would like to share with your CFO (can you think of different data you might be able to use to get a better sense of the write-offs)?
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