carefully weigh the data before casting your vote. As you review the data, you ask yourself, Assuming both teams handled roughly the same number of customers, which chart impresses me more? Which team is the most consistent? Which team, over time, has better average scores? Growing scores? Declining scores? What does the Descriptive Statistics ToolPak tell me about the data? Which team is showing improvement? Can I estimate (or visually predict using the best fit line) which team will have better future performance? If so, which team? How do I know? …and, for whom should I vote?
carefully weigh the data before casting your vote. As you review the data, you ask yourself, Assuming both teams handled roughly the same number of customers, which chart impresses me more? Which team is the most consistent? Which team, over time, has better average scores? Growing scores? Declining scores? What does the Descriptive Statistics ToolPak tell me about the data? Which team is showing improvement? Can I estimate (or visually predict using the best fit line) which team will have better future performance? If so, which team? How do I know? …and, for whom should I vote?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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carefully weigh the data before casting your vote. As you review the data, you ask yourself,
- Assuming both teams handled roughly the same number of customers, which chart impresses me more?
- Which team is the most consistent?
- Which team, over time, has better average scores? Growing scores? Declining scores?
- What does the
Descriptive Statistics ToolPak tell me about the data? - Which team is showing improvement?
- Can I estimate (or visually predict using the best fit line) which team will have better future performance? If so, which team? How do I know?
…and, for whom should I vote?
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