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Cheat Sheet / Updated 02-26-2024
No matter if you're a quantitative finance novice or an expert, this Cheat Sheet can make sense of some equations and terms that you'll use on a regular basis. The following demystifies and explains some of the complexities and models. You can refer regularly to this information to help you in your quant adventures.
View Cheat SheetCheat Sheet / Updated 12-21-2023
Statistics make it possible to analyze real-world business problems with actual data so that you can determine if a marketing strategy is really working, how much a company should charge for its products, or any of a million other practical questions. The science of statistics uses regression analysis, hypothesis testing, sampling distributions, and more to ensure accurate data analysis.
View Cheat SheetCheat Sheet / Updated 10-05-2023
Accountants keep the books of businesses, not-for-profits, and government entities by following systematic methods of recording all financial activities. If you invest your hard-earned money in a private business or a real estate venture, save money in a credit union, or are a member of a nonprofit association or organization, you likely receive regular financial reports. You should read these financial reports carefully, but if you don’t — or if you do but don’t understand what you’re reading — this Cheat Sheet can help you understand the language and necessity of accounting.
View Cheat SheetCheat Sheet / Updated 09-05-2023
To stay organized and on top of your nonprofit’s bookkeeping and accounting responsibilities, timely complete accounting tasks need to be done daily, weekly, quarterly, and yearly. Keep necessary financial information up to date so you’re prepared to submit paperwork to your independent certified public accountant (CPA), the government, and all stakeholders, both within and outside your nonprofit organization. To ensure your nonprofit’s activities are completed, organize a to-do list, prioritizing the tasks so the important ones are done first, and other jobs are scheduled around them. Managing your nonprofit means sticking to your plan to stay organized and run efficiently. Apply these guidelines to your nonprofit’s weekly plan: Set up daily priorities. Knowing what you need to accomplish each day allows you to take care of the most pressing matters. Surround yourself with professional staff. Surrounding yourself with professionals eliminates the pettiness of daily office drama! Professionals are self-motivated and focused on doing their jobs, and they require minimum supervision. Keep your goals before you. To maintain a clear vision, keep your eyes on the prize. Post your vision or your goals in a place where they’re visible to you every day. Manage your time by planning and scheduling your daily activities. Be mindful of distractions that pull you away from completing your tasks. Stay out of politics. Avoiding politics at work protects your nonprofit’s status.
View Cheat SheetArticle / Updated 08-01-2023
When cost accounting, you put together your budgeting process for indirect costs with a plan for direct costs. Think of the combined process as normal costing. This is an important point: You trace direct costs and allocate indirect costs. Normal costing combines indirect cost rate with actual production. The process gets you closer to actual total costs for your product. Here are the two steps to implement normal costing: Direct costs: Traced to the cost object by multiplying (actual prices/rates) x (actual quantity for a specific job object) Indirect costs: Allocated to the cost object multiplying (predetermined or budgeted indirect cost rate) x (actual quantity for a specific job object) Note that both direct and indirect costs use actual quantity in the formula. While you come up with an indirect cost rate in planning, the rate is multiplied by actual quantities. In this case, the quantity is jobs for the month. A job cost sheet lists every cost you’ve incurred for a particular job. That includes direct material, direct labor, and all indirect costs. The job cost sheet is your basis for computing your sale price and your profit. You use this document to prepare a cost estimate for a client. Here is a job cost sheet using normal costing for a landscaping job. Normal Job Cost Sheet — Landscaping Job Type of Cost Amount or Quantity Price or Rate Total Cost (Rounded) Direct material 100 square feet of grass seed $12 per square foot $1,200 Direct labor 15 hours of labor $15 per hour $225 Mileage 30 miles driven $0.18 per mile $5 Indirect costs 30 miles driven $5.36 per mile $161 Total job costs $1,591 The indirect cost calculation (vehicle and equipment costs) uses the actual quantity (miles driven) and the estimated rate per mile. The other direct costs on the job sheet use actual quantities and actual prices/rates.
View ArticleArticle / Updated 07-10-2023
You can use the Central Limit Theorem to convert a sampling distribution to a standard normal random variable. Based on the Central Limit Theorem, if you draw samples from a population that is greater than or equal to 30, then the sample mean is a normally distributed random variable. To determine probabilities for the sample mean the standard normal tables requires you to convert to a standard normal random variable. The standard normal distribution is the special case where the mean equals 0, and the standard deviation equals 1. For any normally distributed random variable X with a mean and a standard deviation you find the corresponding standard normal random variable (Z) with the following equation: For the sampling distribution of the corresponding equation is As an example, say that there are 10,000 stocks trading each day on a regional stock exchange. It's known from historical experience that the returns to these stocks have a mean value of 10 percent per year, and a standard deviation of 20 percent per year. An investor chooses to buy a random selection of 100 of these stocks for his portfolio. What's the probability that the mean rate of return among these 100 stocks is greater than 8 percent? The investor's portfolio can be thought of as a sample of stocks chosen from the population of stocks trading on the regional exchange. The first step to finding this probability is to compute the moments of the sampling distribution. Compute the mean: The mean of the sampling distribution equals the population mean. Determine the standard error: This calculation is a little trickier because the standard error depends on the size of the sample relative to the size of the population. In this case, the sample size (n) is 100, while the population size (N) is 10,000. So you first have to compute the sample size relative to the population size, like so: Because 1 percent is less than 5 percent, you don't use the finite population correction factor to compute the standard error. Note that in this case, the value of the finite population correction factor is: Because this value is so close to 1, using the finite population correction factor in this case would have little or no impact on the resulting probabilities. And because the finite population correction factor isn't needed in this case, the standard error is computed as follows: To determine the probability that the sample mean is greater than 8 percent, you must now convert the sample mean into a standard normal random variable using the following equation: To compute the probability that the sample mean is greater than 8 percent, you apply the previous formula as follows: Because these values are substituted into the previous expression as follows: You can calculate this probability by using the properties of the standard normal distribution along with a standard normal table such as this one. Standard Normal Table — Negative Values Z 0.00 0.01 0.02 0.03 –1.3 0.0968 0.0951 0.0934 0.0918 –1.2 0.1151 0.1131 0.1112 0.1093 –1.1 0.1357 0.1335 0.1314 0.1292 –1.0 0.1587 0.1562 0.1539 0.1515 The table shows the probability that a standard normal random variable (designated Z) is less than or equal to a specific value. For example, you can write the probability that (one standard deviation below the mean) as You find the probability from the table with these steps: Locate the first digit before and after the decimal point (–1.0) in the first (Z) column. Find the second digit after the decimal point (0.00) in the second (0.00) column. See where the row and column intersect to find the probability: Because you're actually looking for the probability that Z is greater than or equal to –1, one more step is required. Due to the symmetry of the standard normal distribution, the probability that Z is greater than or equal to a negative value equals one minus the probability that Z is less than or equal to the same negative value. For example, This is because are complementary events. This means that Z must either be greater than or equal to –2 or less than or equal to –2. Therefore, This is true because the occurrence of one of these events is certain, and the probability of a certain event is 1. After algebraically rewriting this equation, you end up with the following result: For the portfolio example, The result shows that there's an 84.13 percent chance that the investor's portfolio will have a mean return greater than 8 percent.
View ArticleCheat Sheet / Updated 07-06-2023
Accounting can be overwhelming at times. This cheat sheet gives you some useful checklists, ratios and rules that you can use both in bookkeeping and accounting roles. Keep them to hand.
View Cheat SheetArticle / Updated 05-03-2023
After you estimate the population regression line, you can check whether the regression equation makes sense by using the coefficient of determination, also known as R2 (R squared). This is used as a measure of how well the regression equation actually describes the relationship between the dependent variable (Y) and the independent variable (X). It may be the case that there is no real relationship between the dependent and independent variables; simple regression generates results even if this is the case. It is, therefore, important to subject the regression results to some key tests that enable you to determine if the results are reliable. The coefficient of determination, R2, is a statistical measure that shows the proportion of variation explained by the estimated regression line. Variation refers to the sum of the squared differences between the values of Y and the mean value of Y, expressed mathematically as R2 always takes on a value between 0 and 1. The closer R2 is to 1, the better the estimated regression equation fits or explains the relationship between X and Y. The expression is also known as the total sum of squares (TSS). This sum can be divided into the following two categories: Explained sum of squares (ESS): Also known as the explained variation, the ESS is the portion of total variation that measures how well the regression equation explains the relationship between X and Y. You compute the ESS with the formula Residual sum of squares (RSS): This expression is also known as unexplained variation and is the portion of total variation that measures discrepancies (errors) between the actual values of Y and those estimated by the regression equation. You compute the RSS with the formula The smaller the value of RSS relative to ESS, the better the regression line fits or explains the relationship between the dependent and independent variable. Total sum of squares (TSS): The sum of RSS and ESS equals TSS. R2 is the ratio of explained sum of squares (ESS) to total sum of squares (TSS): You can also use this formula: Based on the definition of R2, its value can never be negative. Also, R2 can't be greater than 1, so With simple regression analysis, R2 equals the square of the correlation between X and Y. The coefficient of determination is used as a measure of how well a regression line explains the relationship between a dependent variable (Y) and an independent variable (X). The closer the coefficient of determination is to 1, the more closely the regression line fits the sample data. The coefficient of determination is computed from the sums of squares. These calculations are summarized in the following table. To compute ESS, you subtract the mean value of Y from each of the estimated values of Y; each term is squared and then added together: To compute RSS, you subtract the estimated value of Y from each of the actual values of Y; each term is squared and then added together: To compute TSS, you subtract the mean value of Y from each of the actual values of Y; each term is squared and then added together: Alternatively, you can simply add ESS and RSS to obtain TSS: TSS = ESS + RSS = 0.54 + 0.14 = 0.68 The coefficient of determination (R2) is the ratio of ESS to TSS: This shows that 79.41 percent of the variation in Y is explained by variation in X. Because the coefficient of determination can't exceed 100 percent, a value of 79.41 indicates that the regression line closely matches the actual sample data.
View ArticleCheat Sheet / Updated 04-17-2023
There are several steps to understanding bookkeeping and maintaining a good record of your business’s finances throughout the year. It’s advantageous to get your head around the trickier bits of keeping the books and to know the process in order to better check and control those incomings and outgoings.
View Cheat SheetArticle / Updated 09-15-2022
Financial statement fraud, commonly referred to as "cooking the books," involves deliberately overstating assets, revenues, and profits and/or understating liabilities, expenses, and losses. When a forensic accountant investigates business financial fraud, she looks for red flags or accounting warning signs that indicate suspect business accounting practices. These red flags include the following: Aggressive revenue recognition practices, such as recognizing revenue in earlier periods than when the product was sold or the service was delivered Unusually high revenues and low expenses at period end that can't be attributed to seasonality Growth in inventory that doesn't match growth in sales Improper capitalization of expenses in excess of industry norms Reported earnings that are positive and growing but operating cash flow that's declining Growth in revenues that's far greater than growth in other companies in the same industry or peer group Gross margin or operating margins out of line with peer companies Extensive use of off–balance sheet entities based on relationships that aren't normal in the industry Sudden increases in gross margin or cash flow as compared with the company's prior performance and with industry averages Unusual increases in the book value of assets, such as inventory and receivables Disclosure notes so complex that it's impossible to determine the actual nature of a particular transaction Invoices that go unrecorded in the company's financial books Loans to executives or other related parties that are written off A business that engages in such fraudulent practices stands to lose a tremendous amount of money when penalties and fines, legal costs, the loss of investor confidence, and a tarnished reputation are taken into account.
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