Over the years, there has been emergence of new terminologies instatistics resulting from the introduction of new business practices,notions, and specializations. Both business intelligence and businessanalytics have become common in the last ten years. Hence, it isessential to have a comprehensive understanding of the two factors,and their role in statistical tests and outcomes (Chiang et al.,2012).
Business intelligence represents a broader term, which focuses on thecreation of efficiency during business operations. This occurs afteranalyzing data for a specific period, big data, and from differentsources, with the aim of investigating market problems and solutions.Business intelligence is also essential in projecting information,which affects the internal and external aspects of multiple businessenvironments (Van Der Aalst, 2012).
Business Analytics on the other hand, represents a more complex partof business intelligence. Analytics focuses on the study ofhistorical data, the statistical analysis of several sources, datamining, and using modern methods of prediction of emerging trends inbusiness. As such, business analytics initiates the change of aselection of business practices and functions. Both businessintelligence and analytics complement each other, seeing as businessintelligence investigates data on histories and occurrences, whilebusiness intelligence focuses on predicting the future and directionin business (Chiang et al., 2012).
Sample size is related to statistical tests and outcomes because thesize represents a section of the population required to provideinformation, raw data, and opinions, when proving a given hypothesis.Sample size plays a significant role in the outcome of statisticaltests. To get appropriate results, which show less bias, researchers,are advised to increased their sample size. While small sample sizesare also useful, they do not target different demographics andvariables needed during research (Taddy, 2013). For example, wheninvestigating the rising demand for IT services in a specific area,it is better to sample different demographics such as high schools,collages, different industries, and social settings in order to get acomprehensive understanding of the purchasing and demand history ofIT services. It is important to plan sample size before collectingdata because the size determines the research materials, samplegroup, questions, time, and financial resources needed to carry outthe research in question (Van Der Aalst, 2012).
Chiang, R. H. L., Goes, P., & Stohr, E. A. (2012). “BusinessIntelligence and Analytics Education and Program Development: AUnique Opportunity for the Information Systems Discipline,” ACMTransactions on Management Information Systems, 3(3)
Taddy, M. (2013). “Multinomial Inverse Regression for TextAnalysis”. Journal of American Statistical Association,108.
Van Der Aalst, W. (2012). “Process Mining: Overview andOpportunities,” ACM Transactions on Management InformationSystems, 3(2), 7-17.