02 统计基础与Statistica软件.pptVIP

统计基础与STATISTICA软件 汤吉海 南京工业大学化学化工学院 化工实验楼129# Tel: 8358-7166 E-mail: t.jim@163.com Introduction Introduction There are many aspects of science and engineering problems. Understanding and solving such problems often involves certain quantitative aspects, in particular the acquisition and analysis of data. Treating these quantitative problems effectively involves the use of statistics. Statistics can be viewed as the prescription for making the quantitative learning process effective. The Learning Process The Learning Process (认知过程) An experiment is like a window through which we view nature. Our view is never perfect. The observations that we make are distorted. The imperfections that are included in observations are “noise”. A statistically efficient design reveals the magnitude and characteristics of the noise. It increases the size and improves the clarity of the experimental window. Using a poor design is like seeing blurred shadows behind the window curtains or, even worse, like looking out the wrong window. The Learning Process Learning is an iterative process The Aim Introduction to the general kind of engineering problem and the statistical concepts and methods to be discussed. Case Study introduces a specific example, including actual data. Analysis shows how the data suggest and influence the method of analysis and gives the solution. Many solutions are stepped in detail, and results shown. The problems were solved using available computer programs (e.g., STATISTICA、SAS、SPSS、S-PLUS、MINITAB etc.). Definitions and Basic Concepts Population(总体) and Sample(样本) The sample is a group of n observations actually available. A population is a very large set of N observations (or data values) from which the sample of n observations can be imagined to have come. Random Variable(随机变量) “the value of the next observation in an experiment.” “A random variable is the soul of an observation” and the converse, “An observation is the birth of a random variable.” Expe