《mod5》ppt课件.ppt

Descriptive Statistics allow us to summarize data There are two general types of data, we call: Discrete Continuous/Variable The statistics used to summarize data and the analytical tools we use vary according to the data type. Based on counts Can not be broken down into smaller increments – there are a limited number of possible outcomes. Examples : # of defects, number of days, pass/fail A special form of discrete data, using names to represent categories or possibilities Data that indicates how much or how many precisely At least 10 times better than the value (e.g. minutes for something that takes hours) We describe data with 2 measures Location Dispersion For variable data you may well know these as Average or Mean Variation or Standard Deviation Location The relation of the mean to the target A well located process effectively matches the mean of the result to the target In other words…Centered Dispersion The amount of variation in the process Mean The average of a set of values Strongly affected by extreme values Used for Normal data (variable) Median The midpoint when data is ranked in ascending order Not affected by extreme values Used for non-Normal data (variable) Mode Most frequently occurring value Used for discrete data Range Largest value - smallest value Variance A measure of the average distance each point is away from the mean In statistical speak, the average squared deviation of each individual data point from the mean Standard Deviation The square root of the variance The average distance of the data from the mean n number of measurements x an individual measurement x1, xn the first and last measurements x or x bar mean of the measurements R range ? standard deviation ?2 variance Population refers to all of the things in a given group. Sample refers to a subset of items chosen from the population. Examples Population: all the armature shafts produced from a given lathe.