Description
Business leaders are typically inundated with data. They are challenged to make meaning of an overwhelming amount of information. Additionally, data are often unstructured and difficult to manage, process, and analyze. To solve workplace phenomena, you must know how to look under the hood of your workplace problems and collect the correct type of data for your analysis.
The data you collect can be either qualitative (non-numeric) or quantitative (numeric). Or, you can use a mixed-methods approach, which means that you collect both qualitative and quantitative data from multiple sources of evidence. Even with large amounts of data at your disposal—with the right methodology—you can gather the answers you need from a small sample of your studied population.
The data that leads to logical and meaningful outcomes becomes information. However, you must consider if that information is both reliable and valid. To be reliable, other researchers in your field or colleagues should be able to get the same results when following the research protocol that you used. To be valid, the outcomes must accurately represent the characteristics and variations in the social and physical world. Additionally, it is important to know the difference between correlation and causation when making data-driven decisions.
Please take a moment to watch this short video (1:43) explaining correlation and causation—and learn why increased ice cream sales do not cause an increase in homicides.
When you blend experience, data, and scholarly works, you have new knowledge that can be applied in action to solve your workplace-based problems.
Instructions
Now that you have run your data, you are ready to review it. Let’s reflect on your context of being in a leadership role trying to contribute towards broader economic development efforts. During the linear regression phase of your analysis, you notice that the variables:
Skills, knowledge, and abilities Supply chain industry
Are associated with the variables
Growth Expansion
You hypothesized that skills, knowledge, and abilities isolated in the supply chain management industry are associated with regional growth and expansion. In fact, the R2 number was .812. To test your hypothesis, you ran a Chi-Square Pearson test, which presented you with a sig of .001. Explain if this relationship is causation or correlation and why.
Given that you have been researching how the university plays a role in economic development, the executives from E-Hospital consult with you to determine how they can contribute as well. How would you guide them to select variables for a regression analysis and neural network?
You decide to show them the TensorFlow playground to show them how the neural network will play a role in understanding their data and its impact on the local economy. Navigate to the TensorFlow playground. What are the top three things that you will show them on the website? Why did you choose these?