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Bootcamp Final Exam

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Question 1 of 25

1. Question
When measuring usability:
- It’s important to measure both attitudes and actions
- It’s always most important to measure actions
- It’s always most important to measure attitudes
- You must measure loyalty
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Question 2 of 25

2. Question
The key objective usability metrics at the task level are:
- Completion rates and times
- Ratings of ease and confidence
- Number of times participants stop thinking aloud and number of requests for help
- Ratings of ease and usefulness
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Question 3 of 25

3. Question
The most important subjective usability metric to capture at the task level is:
- The Single Ease Question (SEQ)
- Successful task completion
- How much time it took to complete the task
- A likeability rating
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Question 4 of 25

4. Question
A common way to assess customer loyalty is with:
- The Net Promoter Score (NPS)
- The System Usability Scale (SUS)
- The Usability Metric for User Experience (UMUX)
- The Microsoft Desirability Toolkit
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Question 5 of 25

5. Question
Which questionnaire has items to collect ratings of perceived ease-of-use and perceived usefulness (features meet needs)?
- The UX-Lite
- The System Usability Scale (SUS)
- The Net Promoter Score (NPS)
- The NASA TLX
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Question 6 of 25

6. Question
Which of the following is an example of discrete binomial data?
- Percentage of users successfully making an online purchase
- The 7-point Single Ease Question
- Task completion time
- The System Usability Scale
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Question 7 of 25

7. Question
Which of the following is the best method for evaluating whether users can find a needed function?
- Tree Test
- Card Sort
- Survey
- Focus Group
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Question 8 of 25

8. Question
Which participant characteristic tends to have the biggest impact on UX metrics?
- Prior experience
- Age
- Gender
- Number of children
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Question 9 of 25

9. Question
When working with panels:
- Avoid changing panels when making comparisons over time
- Don’t worry about cheaters or speeders because they are very rare (< 1%)
- Feel free to change panels because UX metrics from different panels vary < 1%
- Don’t work with panels because the incidence of cheating/speeding is almost 90%
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Question 10 of 25

10. Question
In a top task survey, you should:
- Randomize the order of presentation of tasks
- Ask participants to list their single most common task
- Have participants rank all of the tasks in order of importance
- Have participants rank all of the tasks by their frequency of use
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Question 11 of 25

11. Question
For unmoderated usability testing, two ways to validate successful task completion are:
- Multiple choice questions or url matching
- Multiple choice questions or post-completion interviews with participants
- Post-completion interviews with participants or url matching
- It isn't possible to validate successful task completion in unmoderated usability testing
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Question 12 of 25

12. Question
The fundamental metrics for individual usability problems are:
- Frequency and severity
- Frequency and learnability
- Learnability and severity
- Learnability, frequency, and severity
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Question 13 of 25

13. Question
All other things being equal, which data set will have a wider confidence interval?
- Sample Size (n) = 15
- Sample Size (n) = 150
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Question 14 of 25

14. Question
All other things being equal, which analysis will produce a wider confidence interval?
- 95% Confidence Level
- 85% Confidence Level
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Question 15 of 25

15. Question
The width of a confidence interval is:
- Two margins of error
- Two standard errors
- Four margins of error
- One standard deviation
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Question 16 of 25

16. Question
Which of the following statements is true?
- The type of data matters when selecting a confidence interval method
- The type of data does not matter when computing confidence intervals
- Rating scale data requires log transformation before it can be analyzed
- Confidence intervals for discrete-binary data are based on the geometric mean
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Question 17 of 25

17. Question
You get a p-value of .01 and conclude the designs are different. What error can you make?
- Type I
- Type II
- Both Type I and Type II
- Neither Type I nor Type II
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Question 18 of 25

18. Question
Which of the following is true about formal hypothesis testing?
- There are two ways to be right and two ways to be wrong
- Hypothesis testing is infallible
- A Type II error is always worse than a Type I error
- The worst error is the Type V error
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Question 19 of 25

19. Question
You want to compare SUS (System Usability Scale) data you collected from 10 participants who used the current design and 9 other participants who used a new design. Which type of test should you run?
- Between-subjects t-test
- Test against a binary benchmark
- Within-subjects t-test
- N-1 Two Proportion Z Test
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Question 20 of 25

20. Question
You’ve run a usability study of your online retail site in which 13/15 participants successfully completed an online purchase. In a study of the same task with a competitor’s website, there were 5 successes out of 9 participants. You want to know if the success rate with your design is significantly better than with the competitive design. What type of test should you use to analyze the data?
- A/B (N-1 Two-Proportion) Test
- Between-subjects t-test
- Within-subjects t-test
- Binomial test against a benchmark value
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Question 21 of 25

21. Question
All other things being equal, which decision will require a larger sample size?
- Testing with 99% confidence (p < .01)
- Testing with 95% confidence (p < .05)
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Question 22 of 25

22. Question
All other things being equal, which decision will require a larger sample size?
- Set power to 80%
- Set power to 50%
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Question 23 of 25

23. Question
All other things being equal, which decision will require a larger sample size?
- Need compelling evidence of a small difference
- Need compelling evidence of a large difference
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Question 24 of 25

24. Question
The “20/20” rule of precision refers to the observation that:
- The typical margin of error with n=20 is about 20%
- The lower the p value, the harder it is to see significant results
- When you set power to 50%, the associated value of Z disappears from sample size formulas
- If you don't look for problems, you'll never find them
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Question 25 of 25

25. Question
To cut a margin of error approximately in half, you need to:
- Quadruple the sample size
- Double the sample size
- Cut the sample size in half
- Multiply the sample size by ten
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