Module 1.4.2 Quiz – Data Analytic Projects Answers
1. A college has deployed next-generation analytics. Which question would most likely be answered by next generation analytics that could not be answered by traditional analysis tools?
- Which class has the most sections available?
- What are the 10 most expensive textbooks required in any class?
- Which 100 classes fill the fastest once open enrollment is available for the general population?
- Which teacher had the highest number of students enrolled in classes during the last year?
- Which class sections do students consider the most in the online environment without actually enrolling?
Explanation: Structured data would be able to answer questions related to how many sections, textbook prices, or enrollment statistics such as courses that fill the quickest or the most number of students. Next generation analytics takes data analysis a step forward in analyzing browsing habits and predictive analytics based on prior data and current data in real time.
2. A college uses a learning management system (LMS) to host lecture materials and provide access to assignments and assessments. A teacher uses the LMS to check activities completed by students in a particular course. Which data analytics method is being used?
- indicative
- predictive
- descriptive
- prescriptive
- proactive
Explanation: Data analytics, applied to Big Data, can be classified in three major types:
- Descriptive – provides information about the past state or performance of a person or an organization
- Predictive – attempts to predict the future, based on data and analysis, or what will happen next
- Prescriptive – predicts outcomes and suggests courses of actions that will hold the greatest benefit to an organization
In this case, the teacher uses the existing data to check the progress of students.
3. A large online ordering company collects the sales history of its customers. Using this historical data, the online company sends customized sales advertisements to a specific group of customers. Which data analytics method is being used?
- indicative
- predictive
- descriptive
- prescriptive
Explanation: Data analytics, applied to Big Data, can be classified into three major types:
- Descriptive – provides information about the past state or performance of a person or an organization
- Predictive – attempts to predict the future, based on data and analysis, or what will happen next
- Prescriptive – predicts outcomes and suggests courses of actions that will hold the greatest benefit to an organization
In this case, the company predicts the customers who are more likely to purchase similar products, and sends those customers the targeted sales advertisements.
4. What is an example of descriptive data analysis?
- predicted oil price increases
- control of highway traffic signals
- an hourly traffic report for a highway
- a weather forecast description
Explanation: An example of descriptive data analytics is an hourly highway traffic report because it is based on historical data (traffic patterns over the last hour for example) but does not use that analysis to predict or control future events. Predicted oil price increases and a weather forecast are both examples of predictive data analytics. The use of data analytics to control highway traffic signals is an example of prescriptive data analytics.
5. What is a benefit of analyzing data in motion rather than a static data set?
- Critical decisions can be made more quickly.
- The data is more accurate.
- All historical data is used to arrive at a decision.
- The data is more structured.
Explanation: Analysis using a static data set uses historical data. Data in motion uses historical data as well as data from sensors, users, machines or any related data that is generated in real time. A benefit of using data in motion is that analysis is being performed on real time data, which provides quicker more accurate results.
6. Which type of results do data analysts calculate from larger datasets to inform decision making?
- converged
- numerous
- varied
- accurate
Explanation: Larger datasets allow the data analyst to calculate much more accurate results to inform decision making.
7. What is a characteristic of predictive data analysis?
- establishes a future trend line based on past data
- uses simple math models
- uses a feedback system to track outcome of actions taken
- based solely on historical data
Explanation: Predictive analytics is useful when trying to predict the future, based on collected data and statistical techniques. Predictive analytics is also useful when trying to infer missing data and when establishing future trend lines based on past data.
8. Match the step in the Data Analysis Lifecycle with the description.
Explanation: Place the options in the following order:
| Investigating the Data | determining if the data is valid, complete and relevant |
| Analyzing the Data | identifying patterns and correlations contained in the data to produce conclusions |
| Preparing the Data | transforming the data into a format appropriate for analysis |
| Asking the Question | defining the problem to be solved or purpose of the analysis |
| Presenting the Data | communicating insights derived from the analysis to decision makers |
| Getting the Data | locating the data and determining if there is enough data to complete the analysis |
9. What is the first step in any analytic project?
- defining the goal of the project
- finding relevant data for analysis
- creating representative charts and graphs
- making recommendations for changes
Explanation: In the first step of any analytic project, the goal of the project is defined. Goals for projects can be based on external (client) or internal (stakeholder) business requirements. Understanding the goals of the project is key to successful data analysis.