introduction to data analytics coursera quiz answers week 4
Analyzing and Mining Data
Practice Quiz
1. What is one of the common measures of Central Tendency?
- Variance
- Regression
- Classification
- Mean
2. What technique is used to help identify the nature of the relationship between two variables?
- Regression
- Anomaly Detection
- Clustering
- Classification
Graded Quiz
4. What is a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of numerical or quantitative data?
- Pie
- Statistics
- Algebra
- Calculus
5. Data Mining is defined as the process of:
- Filtering data based on pre-defined criteria
- Preparing raw data for analysis
- Extracting knowledge from data
- Identifying errors in data
6. What type of data mining operations was R specifically built to handle?
- Classification of data
- Filtering
- Sorting
- Calculating mean, median, and mode
7. When you’re calculating the middle value of a data field in a data set, what are you really calculating?
- Average
- Mode
- Mean
- Median
8. What is the general tendency of a set of data to change over time called?
- Trend
- Pattern
- Variation
- Anomaly
Communicating Data Analysis Findings
Practice Quiz
9. Data visualizations such as graphs and charts are a great way to bring data to life.
- True
- False
10. You can use dashboards to present operational data such as daily progress data, as well as analytical data, such as the overall health of a business function.
- True
- False
11. What spreadsheet software is preferred when multiple users need to collaborate?
- Tableau
- Microsoft Excel
- Google Sheets
- R-Studio
Graded Quiz
12. "A presentation is not a data dump”. What is the one thing you would do to ensure your presentation is not a data dump?
- Include only that information as is needed to address the business problem
- Not include facts and figures in the presentation
- Deliver the findings in a single slide
- Not use visuals in the presentation
13. What is the discipline of communicating information through the use of visual elements?
- Data type conversion
- Data visualization
- Data regression
- Data profiling
15. What is the goal of Data Visualization?
- Make collaboration easy
- Establish trust in the audience
- Make information easy to comprehend, interpret, and retain
- Make the presentation look attractive
16. What can you do to help your audience trust you?
- Hand them copies of the data sets you have used for analysis
- Make your presentation look good
- Share your data sources, hypotheses, and validations
- Share the detailed documentation of every aspect of your project so they can verify all details
