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Chap 11 Engineering Statistics PREP004 – Introduction to Applied Engineering College of Engineering - University of Hail Fall 2009 Statistics Statistics is the area of science that deals with collection, organization, analysis, and interpretation of data. It also deals with methods and techniques that can be used to draw conclusions about the characteristics of a large number of data points-commonly called a population– By using a smaller subset of the entire data. For Example… You work in a cell phone factory and are asked to remove cell phones at random off of the assembly line and turn it on and off. Each time you remove a cell phone and turn it on and off, you are conducting a random experiment. Each time you pick up a phone is a trial and the result is called an outcome. If you check 200 phones, and you find 5 bad phones, then relative frequency of failure = 5/200 = 0.025=2.5% Statistics in Engineering Engineers apply physical and chemical laws and mathematics to design, develop, test, and supervise various products and services. Engineers perform tests to learn how things behave under stress, and at what point they might fail. Statistics in Engineering As engineers perform experiments, they collect data that can be used to explain relationships better and to reveal information about the quality of products and services they provide. Statistics : Major Engineering Areas Quality control and process control use statistics as a tool to manage conformance to specifications of manufacturing processes and their products. Design of Experiments (DOE) uses statistical techniques to test and construct models of engineering components and systems. Time and methods engineering use statistics to study repetitive operations in manufacturing in order to set standards and find optimum procedures. Reliability engineering which measures the ability of a system to perform for its intended function (and time) and has tools for improving performance. Probabilistic design involving the use of probability in product and system design Frequency Distribution: Scores for an engineering class are as follows: 58, 95, 80, 75, 68, 97, 60, 85, 75, 88, 90, 78, 62, 83, 73, 70, 70, 85, 65, 75, 53, 62, 56, 72, 79 To better assess the success of the class, we make a frequency chart or a Histogram: With Statistics the information can be better analyzed. The data are presented in a frequency distribution or histogram. Divide each no. by 26 Analysis of Histograms Graph A is class distribution of numbers 1-10 Graph B is class distribution of semester credits Data for A = 5.64 +/- 2.6 (much greater spread than B) Data for B = 15.7 +/- 1.96 (smaller spread) Skew of A = -0.16 and Skew B = 0.146 CV of A = 0.461 and CV of B = 0.125 (CV = SD/Mean) Frequency B Frequency A 9 8 7 6 5 4 3 2 1 0 7 6 5 4 3 2 1 0 2 3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 Measures of Central Tendency & Variation Central Tendency Measures: Mean (Average) , and Median, Mode 1 n x xi n i1 Variation and Dispersion Measures: Range R, Standard Deviation and Variance n R = Xmax - Xmin s i1 (x i x ) 2 n 1 Normal Distribution Any probability distribution with a bell-shaped curve is called a normal distribution. The detailed shape of a normal distribution curve is determined by its mean and standard deviation values. THE NORMAL CURVE zi = (xi - x) / s approx. 68% of the data will fall in the interval of -s to s, one std deviation ~ 95% of the data falls between -2s to 2s, and approx all of the data points lie between -3s to 3s Normal Curve has many applications in Engineering : Product design, Quality, Reliability, Engineering Statistical Software : Microsoft Excel Statistics in Excel 1 Select Tools/Data Analysis Business Statistics: A DecisionMaking Approach, 6e © 2005 Prentice-Hall, Inc. Chap 2-14 Histograms in Excel (continued) 2 Choose Histogram 3 Input data and bin ranges Select Chart Output Business Statistics: A DecisionMaking Approach, 6e © 2005 Prentice-Hall, Inc. Chap 2-15 Engineering Statistical Software : Minitab Home Work 7 Use Excel to determine the average, the range and the standard deviation of the following set of numbers: (a) 24, 35, 17, 21, 24, 37, 26 (b) 59.4, 51.3, 84.15 , 96.3 ,71.1 , 95.4 78.75 , 66.15 ,77.85 Chapter Summary Data in raw form are usually not easy to use for decision making -- Some type of organization is needed: Table Graph Techniques reviewed in this chapter: Frequency Distributions, Histograms Many Other Tools are available (Scatter Diagrams and Control Charts, Pareto diagram etc…) Engineer use computer software to perform statistical calculations and data analysis.