SPC初阶培训.ppt

* G. STATISTICS -- Participant Workbook, page 18 To learn more about the data we collect, we can use statistics. Statistics are just numbers we calculate from our data that help us draw conclusions and make decisions. We read about statistics in the newspaper every day -- crime rates or the average price of a home are two examples. In other words, statistics help us better understand the variation in our processes and products. We’re going to learn about two types of statistics in this module. The first type of statistic is called the measure of central tendency. That’s a fancy mathematical term, but it’s really quite simple to understand. The measure of central tendency tells us what the typical value is for a group of data. It’s called the average. To illustrate these statistics, let’s use age as an example. Perhaps we want to know the typical age of people in this group. To learn that, I could ask each of you to write your age down on a sheet of paper. I could calculate the average age by adding up all of your ages and dividing by the number of people in the room. PRESS DOWN ARROW KEY TO ANIMATE SLIDE. In the example on the slide, the average age of the five people is 38 years. Question: Do any of you calculate averages for data you collect from your processes? What are some examples? Possible answers: Average circuit width, average temperature, average number of defects on a board * G. STATISTICS -- Participant Workbook, page 18 The next type of statistic is a measure of spread. These measures just tell us how far apart the data are. Are the data very close in value or very different? In other words, these measures tell us how much variation there is in a set of data. One way to determine how far apart the data is to calculate a range. To illustrate, let’s continue with our age example. To calculate the age range, we just subtract the youngest age (27) from the oldest age (57) to get a range of 30 years. PRESS DOWN ARROW KEY TO ANIMATE SLI