Please submit in a word document.
1. Define Analytics.
2. Describe the differences between descriptive, predictive, and prescriptive analytics
3. How do Quantitative and Qualitative data differ? Can you perform analytics on both types?
4. Define the 3 stages (and 6 steps) of quantitative Analysis. Provide a brief summary of each stage and step.
5. Do you consider yourself analytical, why or why not? If you do not consider yourself analytical, what other strengths do you have that would also support the role of a data analytics?
6. Analytics can answer many questions. Six key questions are listed in Figure 1-1. Which cell in the 2×3 table describes the type of questions that generally interest you most and why? Is there a question in your current (or past) company/organization that would fall within one of these categories? You can also use the university as an example of an organization. What is the question you would like to answer?
7. Analytics is not always the best approach to make a decision or solve a problem. Please review the examples that describe when analytics are not practical. Do your best to come up with a real world example for each of those five categories.
8. Several types of log and process errors are listed in the table titled Typical Decision -Making Errors. Which errors do you think should be of greatest concern in relation to a data project.
9. In one of the readings there is an example of a pilot who discussed the analytics used in his cockpit. He said I still occasionally find it useful to look out the window. What do you think the pilot meant by this, and how could you apply it to your role as a data analyst or decision maker in an organization?
10. Give a brief elevator pitch (written) on why analytics should be used by business?
