Statistical Approach to Business Decisions
Statistical research in business makes it easy for managers to evaluate past performances, forecast future business practices, and effectively lead their organizations. Statistics can help describe markets, set prices, inform advertising, and respond to consumer demand (Amrhein, Trafimow, & Greenland, 2019). Descriptive statistics tell data analysis, which helps show, describe, or summarize information in a meaningful way (Simonsohn, Simmons, & Nelson, 2019). Descriptive statistics are crucial because presenting raw data would make it hard for one to visualize what the data illustrates. Therefore, descriptive statistics interpret data simple. Descriptive statistics is thus essential in making business decisions as it provides facts about the past and helps explain the reason behind it. Through such historical data, managers ate able to evaluate past business successes and failures and make better decisions.
Inferential statistics make conclusions concerning populations using data acquired from the population. Rather than using the general population to collect data, statisticians collect samples from many residents and make conclusions concerning the general population using the collected sample (Amrhein, Trafimow, & Greenland, 2019). Probability distributions, correlation testing, regression analysis, and hypothesis testing all fall under the inferential statistics category. Managers use inferential statistics in business to help them draw better conclusions on whether a particular phenomenon, e.g., relative demand or work satisfaction among competing brands, measured in a sample, can be logically generalized to a population. Understanding the relationship between sales and advertising is significant in marketing research (Ogbari et al., 2016). Therefore, through inferential statistics, a sample of randomly chosen advertising and sales figures for a particular company over a specific period would be useful in providing inferences and implications about the underlying process, i.e., the overall connection between the organization’s level of advertising and their level of sales. Understanding the actual relationship between sales and advertising of the company’s sample data would help managers foretell sales for any level of advertising and set advertising at a level that optimizes profits.
References
Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2019). Specification curve: Descriptive and inferential statistics on all reasonable specifications. Available at SSRN 2694998.
Ogbari, M. E., Oke, A. O., Ibukunoluwa, A. A., Ajagbe, M. A., & Ologbo, A. C. (2016). Entrepreneurship and business ethics: Implications on corporate performance. International Journal of Economics and Financial Issues, 6(3S), 50-58.
Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician, 73(sup1), 262-270.