How Accountants Use Statistics
| Accounting.com Staff
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In an age of big data, statistical analysis is becoming an increasingly powerful tool for almost all accounting professionals. In fact, the importance of statistics in accounting can't be overstated. Taking a course in statistics helps every accountant improve their efficiency while helping their clients make better decisions.
Below, we take a look at the varied uses of statistics in accounting and the types of accountants who rely on this powerful tool.
The Varied Uses of Statistics in Accounting
Accountants who perform audits benefit greatly from understanding and using statistical analysis. For example, when conducting a reliability assessment, one of the accountant’s first tasks is to gather evidence. Auditors know that the easiest way to do this is by looking at a portion of the whole, rather than gathering every bit of data available. Statistically representative samples are preferred in this area as they help auditors work more efficiently and objectively.
Accounting standards are front and center when managers determine retirement and other benefits. Accountants set premium adjustments to account for future risk and artificial fluctuations in short-term interest rates using statistical models and methods. Recently, for example, accountants and others with the American Benefits Council used historical statistical data to develop policy recommendations to help control defined benefit plans and promote retirement security.
Jacks-of-all-trades, controllers typically work for a single company, overseeing all of its finances including cost analyses, budget reports, and forecasting. Controllers may also provide financial analysis and advice to the head of the organization. Having a thorough understanding of the statistical principles used in creating analyses and forecasts, controllers ensure that their organization operates profitably and efficiently.
Accountants use statistics to forecast consumption, earnings, cash flow, and book value. Considered accounting for the future, forecasting involves an amount of guesswork about the future — and when people guess, they frequently make errors. Having a thorough understanding of the distribution and metrics for evaluating potential errors, accountants are better able to more efficiently make predictions about the future.
The detectives of the accounting world, forensic accountants use accounting and legal principles to ferret out financial fraud and deceit. With today’s incredibly complicated financial instruments like credit default swaps and collateral debt obligations, forensic accountants need to understand how statistical principles are used to value and anticipate risk in these and other securitization products.
With foreclosure risk high for some homeowners, anticipating and predicting the risks associated with any given loan has never been more important. Mortgage underwriters assess that risk and, therefore, need to have a thorough understanding of statistics in order to set a premium price that is reasonable for the borrower and profitable for the lender.
Hand in glove with forecasting is risk management or actuarial accounting. Accountants are frequently required to specify a premium that reflects the risk, or range of error, with any given forecast. Known as the discount rate, accountants often use statistical principles, such as correlation and distribution, to anticipate this risk and account for it when setting a valuation. More recently, accountants are using more sophisticated statistical techniques, such as covariance and beta models, to limit valuation error.
Accounting Statistics: Resources for Professionals
Accountants can find the latest research on applied and pure statistical analysis in accounting from Contemporary Accounting Research (CAR) and the Journal of Financial and Strategic Decisions. The National Center for Education Statistics (NCES) provides links to statistical data made available from various government agencies.
Accounting Statistics: Resources for Students
Would-be accounting students can get started on their exploration of statistics with these free and open introductory online courses:
Coursera, which offers courses from top universities like Duke, CalTech, Johns Hopkins, Columbia, and Princeton, has a variety of statistics courses including Introduction to Statistics and Econometrics: Methods and Applications. More complex, the latter course offers students instruction in translating data into models to create forecasts and explores the differences between binary choice data and time series data, among other things.
The Massachusetts Institute of Technology (MIT) shares its course materials online at MIT OpenCourseware. Among these materials, readers will find the full coursework from MIT’s Introduction to Probability and Statistics course. In addition to text materials, students can download lecture notes and exams. This course covers probability models and distributions, random variables, statistical estimation and testing, confidence intervals, and linear regression.
With Udacity’s Introduction to Statistics, students learn to visualize data relationships, estimate, determine probability, and examine distribution including the normal distribution and outliers. They also learn about hypothesis testing, confidence intervals, and linear regression.
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