datatypesandbasicdefinitions(英文版)-資料下載頁
2025-01-06 07:41本頁面
【正文】 ty results from ining measurements on interposers. – Continuous. – ‘Open/Short’ data from a substrate supplier’s end of line manufacturing process. – Discrete, Nominal. – Underfill material viscosity from supplier. – Continuous. Discussion Scenarios (Continued) Ent it y T h ick n es s D ate Pr o d u ct Lot Particl es 1 W S T 0 1 39 4 97 0 11 8 85 4CS 1C 15 4 22 4 90 24 2 W S T 0 3 38 4 97 0 12 4 85 4CS 1C 15 4 22 5 60 21 3 W S T 0 1 39 6 97 0 20 5 85 4CS 1C 15 5 23 5 90 28 4 W S T 0 1 40 2 97 0 20 8 85 4CS 1C 15 6 24 5 90 20 Scenario 2 ? Below is an example of a file containing process data from the factory. Identify each of the variables as Nominal, Ordinal or Continuous. – Entity: Nominal. – Thickness: Continuous. – Date: Continuous – measurements of time. – Product: Nominal. ? Lot: Ordinal. ? Particles: Continuous – for analysis purposes. Practice Items 1. Describe a critical difference between continuous and discrete data. ? Discrete data is counted in whole numbers or categories while continuous data is a data type where the measurement could fall anywhere on the measurement scale. 2. Why is it so important to identify a data type correctly? ? Because different data types require different types of analysis and reporting. Lesson 2 Summary – Population = All members of a specified group. – Sample = Subset of a specified group of data. – Variable = Any characteristic of a person or thing. – Quality Characteristic = Specific variable on which information will be collected. – Value = Actual number. – Continuous Data = Measured values along a continuum. – Discrete Data = Categorical data. – Nominal Data = Unordered discrete data. – Ordinal Data = Ordered discrete data. 演講完畢，謝謝觀看！
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