Descriptive statistics vs. inferential statistics

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Accounting students and professionals alike need to have a strong understanding of a variety of financial, statistical, and computational concepts. Analysis of financial data and deriving actionable insights are especially important. Students seeking to earn an accounting degree online should have a strong understanding of the concepts that drive different types of statistics. Consider how descriptive statistics and inferential statistics can both apply to the many roles tied to accounting, as well as the important differences between them.

A close-up view of statistical graphs on a tablet.

What is descriptive statistics?

Descriptive statistics refers to the use of representative or sample sets of data to derive a conclusion or finding. In descriptive statistics, the determinations reached are only applied to the population or data set being studied.

Descriptive statistic examples can be found in many industries and situations. In sports, descriptive statistics could be used in gathering information about a basketball player’s performance based on the individual numbers tallied, such as points scored, blocks, and rebounds, during a single game or series of games. With analysis, this data can be used to compare the player to others who also had the same performance numbers collected. However, the statistics gathered and information generated about these players should not be applied to all professional basketball players, or all players in general. Descriptive statistics are limited to the population defined through the data initially gathered. They don’t generally aim to reach a conclusion or provide proof of a larger point based on the result.

Descriptive statistics could also be used in the academic world in primary, secondary, and higher education to analyze student grades by teachers and professors. An educator may track performance and present anonymous group results to an entire class, helping them understand how they performed not only on a letter grade or points basis but also compared to fellow students. The educator may share the mean, median, and mode grade to help students contextualize individual performance, as well as measure the range or standard deviation of the scores. This information may prove helpful to educators, helping them benchmark performance and compare it to other classes or students.

In terms of finance and accounting, descriptive statistics can be useful to better understand return on investment, Investopedia explains. Although the results of this type of statistical analysis can’t be counted upon to predict the future, they describe core tendencies that occur over time.

What is inferential statistics?

One simple definition of inferential statistics is taking a sample that is representative of a population and then drawing a conclusion for that larger group. This requires careful calculations to analyze the statistics correctly and ensure the connection between population and sample size is accurately represented, often through additional tests and mathematical work. This form of statistics is frequently used in the social sciences and draws on a number of complicated techniques such as linear regression analysis and structural equation modelling, Thought Co. explains. Because the analysis relies on a sample as opposed to the entire population, a degree of confidence in the result of the statistical analysis is expressed by the professionals who engaged in the process.

Some inferential statistics examples include determinations about widespread economic and health care considerations for populations across states or the entire country. Political polling, which sets a sample size and then extrapolates vote predictions for specific candidates in individual elections, is another way in which this type of statistics is used. Sentiment polling about everything from political affiliation to eating preferences and frequency of attending a sporting event or visiting a movie theater are other examples.

In the world of finance and accounting, inferential statistics are valuable for reaching conclusions in situations where a full analysis of the data is prohibitive or impossible. This type of statistics may be used to make determinations about customer groups, especially for large businesses. Many potential uses arise when professionals consider factors outside of the business itself. While many modern, mature companies have access to strong data sets about internal operations, that’s not true for external needs. An analysis of a potential investment or purchase of a competing or complementary organization could draw on inferential statistics to examine a sample of similar situations involving other businesses and derive specific results that inform future actions.

Building a base of statistical competence for your accounting career

Accountants in many roles may use descriptive and inferential statistics in a variety of different applications, depending on the professional path they choose. Developing foundational knowledge about these two core types of statistics helps students appear more desirable to potential employers, especially when their day-to-day work focuses in part on utilizing these types of statistical analysis.

The University of Alabama at Birmingham offers an accounting degree online that includes two courses, Quantitative Analysis I and Quantitative Analysis II, which help students develop knowledge in this important area. Along with these specific classes, learners enjoy a flexible educational environment that allows for learning at an individually preferred pace. To learn more about UAB’s educational options for students who want to pursue and accounting career, get in touch with an academic advisor today.

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ThoughtCo.: Inferential Vs. Descriptive Statistics

Investopedia: Descriptive Statistics

DeepAI: Inferential Statistics

UAB Collat School of Business: Bachelor of Science in Accounting

UAB Collat School of Business: Course Descriptions BACC