BUS308 Assignments Week 3 - Discussion 2

Hello Class,

In reading lecture 2 this week and focusing on understanding how to interpret the outcomes of both test, I was surprised that ANOVA is somewhat robust around violations on the variance equality assumption and may still produce acceptable results with unequal variances. If it is still able to produce these positive results then it makes me think how much (percentage or range) from the variance equality is acceptable. Perhaps this may not mean anything at all since Excel is doing the calculation for us but could it be significant to provide a false positive?

Additionally, I liked how the ANOVA single factor output provides the summary table of all the groups. This helped visualize that data to make sense of the ANOVA table. I also found very interesting the fact that when the calculated F is greater than the critical F, we reject the null hypothesis. The lecture further states that the critical F or any statistic in an Excel output table is the value that exactly provides a p-value equaling our selected value for Alpha. Last of all, I like the flexibility that the chi-square test provides with when looking at patters or distributions of variables that often help with identifying differences that could be important. The lecture mentions looking at continuous variables and divide any range of variables into groups such as quartiles (4 groups). I believe this is beneficial to be able to submit all available data through the various test and interpret the results into usable information.

These two test (ANOVA and chi-square) definitely enable processing and understanding of big data analytics within the IS/IT field. Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately – an effort that’s slower and less efficient with more traditional business intelligence solutions (SAS, n.d.). This process relies on the help of statistics to identify data significance in the abundance of data availability along with scaling machine learning capabilities.

Interesting information of big data analytics: (definitely worth the read of the full article below)

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. In his report Big Data in Big Companies, IIA Director of Research Tom Davenport interviewed more than 50 businesses to understand how they used big data. He found they got value in the following ways: Cost reduction, faster, better decision making, and new products and services.

~Jay

Reference:

SAS (September 27, 2019). Big data analytics: What it is and why it matters. Retrieved from https://www.sas.com/en_us/insights/analytics/big-data-analytics.html