英文質(zhì)量管理質(zhì)量管理PPT課件

1、Definition of Statistics Statistics is the study of variation, interactions and, operational definitions. Statistics is the study of data to provide a basis for action on a population or process. 第1頁/共39頁Types of Statistical Studies Enumerative studies are statistical investigations that lead to act

2、ion on a static population (that is, a group of items, people, etc. that exist in a given time period and/or at a given location). Analytic studies are statistical investigations that lead to action on a dynamic process. Since this is a text on quality improvement, the primary focus will be on analy

3、tic studies. 第2頁/共39頁Enumerative Studies Basic Concepts A population (or universe) is the totality of units, items, or people of interest that exist in a given time period and/or given location Administration. A frame is a list of the items in a population. The gap is the difference between the fram

4、e and the population. A sample is a portion of the frame under investigation, and is selected so that information can be drawn from it about the frame. 第3頁/共39頁 Basic Concepts Nonrandom samples are selected on the basis of convenience (convenience sample), the opinion of an expert (judgment sample),

5、 or a quota to ensure proportional representation of certain classes of items, units, or people in the sample (quota sample). All nonrandom samples have the same shortcoming theyre subject to an unknown degree of bias in their results. This bias is caused by the absence of a frame. Nonrandom samples

6、 should be used only when better information is too costly to obtain.第4頁/共39頁 Random samples are selected so that every element in the frame has a known probability of selection. Types of random samples include simple, stratified, and cluster. All random samples allow generalized statements to be ma

7、de about the frame from the sample. A random sample is selected by operationally defining a procedure that utilizes random numbers in the selection of the sampled items from the frame to eliminate bias and hold uncertainty within known limits.第5頁/共39頁 Seven steps are involved in selecting a simple r

8、andom sample: Step 1. Count the number of elements in the frame, N. Step 2. Number the elements in the frame from 1 through N. If N is 25, then the elements in the frame should be numbered from 01 through 25. All elements must receive an identification number with the same number of digits.第6頁/共39頁

9、Step 3. Select a page in a table of random numbers. For example, selecting a page and starting point yields.193040092878311398676069611339043462052856735990548709422934276212493869294093第7頁/共39頁Step 4. On the selected page of random numbers, select a column of numbers, select a starting point in tha

10、t column, and use as many digits as there are digits in N (two digits in the case of N = 25). For example, beginning with the top of our column, selecting, and using the first two digits of each number in that column, the first random number is 19.Sample NumberIdentification NumberItems119S209I304D4

11、05E513M612L第8頁/共39頁 Step 5. Determine the necessary sample size. Step 6. From the chosen column on the selected page, select the first six two-digit numbers between 01 and 25, inclusive. If a number is encountered that is smaller than 01 (e.g., 00) or larger than 25 (e.g., 31), ignore the number and

12、 continue down the column. If an acceptable number appears more than once, ignore every repetition and continue moving down the column until six unique numbers between 01 and 25 have been selected. If the bottom of the page is reached before six unique random numbers are obtained, go to the top of t

13、he page and move down the next two-digit column. Step 7. Finally, analyze the information as a basis for action.第9頁/共39頁Two important points to remember are: 1.different methods of measurement will also yield different results. 2.different samples of size six will yield different results, and Random

14、 samples, however, dont have bias, and the sampling error can be held to known limits by increasing the sample size.第10頁/共39頁Conducting an Enumerative Study The following 13 steps present a guide for conducting an enumerative study. The steps are the same whether the study is based on a complete cou

15、nt of the population or a sample.第11頁/共39頁 Step 1. Specify the reason(s) you want to conduct the study (for example, to estimate the average number of sick days per employee in the XYZ Company in 2002). If this average is greater than 8.0 days, then a new health care plan will be instituted. If it i

16、s less than or equal to 8.0 days, the current plan will be maintained. 第12頁/共39頁 Step 2. Specify the population to be studied. In our example, the population would be all full-time employees in the XYZ Company in 2002. An employee is considered full-time in 2001 if he had full-time status designatio

17、n at any time during the year.第13頁/共39頁Step 3. Construct the frame (a list of all full-time employees). Everyone who will use the studys results as a basis for action must agree that the frame represents the population upon which they want to take action.第14頁/共39頁Step 4. Perform secondary research (

18、such as the examination of pre-published data) to determine how much information is already available about the problem under investigation. For example, check the Human Resources Departments records.第15頁/共39頁Step 5. Determine the type of study to be conducted (for example, mail survey, personal int

19、erviews, analysis of units). In this example, we would analyze employee absentee cards for 2002.第16頁/共39頁Step 6. Make it possible for respondents to give clear, understandable information, and/or for the researcher to elicit clear, understandable information. For example, the method for analyzing ab

20、sentee cards should be clear and straightforward. Consider the problem of non-response. In this example, be sure no absentee cards are missing, and make sure the data gatherers know how to interpret the absentee cards.第17頁/共39頁Step 7. Establish the sampling plan to be used, determine the amount of a

21、llowable error in the results, and calculate the cost of the sampling plan. At this stage, Steps 1 and 2 may need revisions due to cost considerations. For example, we may decide to draw a simple random sample of employee absentee cards using random numbers, at a cost of $1 per card, assuming an all

22、owable error of one quarter of a day in the estimate.第18頁/共39頁Step 7 requires a random sample. The result of a nonrandom sample in an enumerative study is worth no more than the reputation of the person who signs the report. 第19頁/共39頁Step 8. Establish procedures to deal with the non-responses and di

23、fferences between interviews, testers, inspectors, and so on. For example, be able to assess differences in collected data due to differences in the data gatherers abilities.第20頁/共39頁Step 9. Prepare unambiguous instructions for the data gatherers that cover all phases of data collection. 第21頁/共39頁St

24、ep 10. Establish plans for data handling, including format of tables, headings, and number of classes.第22頁/共39頁Step 11. Pretest the data-gathering instrument and data-gathering instructions. 第23頁/共39頁Step 12. Conduct the study and the tabulations. It is critical that the study be carried out accordi

25、ng to plans. From the gathered data, calculate the sampling errors of interest. This is important so that the studys users can understand the degree of uncertainty present in the study results. In our example, we would calculate the standard error for the average number of days absent per employee.第

26、24頁/共39頁Step 13. Interpret and publish the results so that decision makers can take appropriate action. For example, if the average number of days absent per employee is greater than eight, then establish the new health care program.第25頁/共39頁Analytic Studies Basic Concepts Analytic studies are stati

27、stical investigations that lead to actions that will improve or innovate a process over time. 第26頁/共39頁 The concept of a population does not exist for an analytic study because future process output, which does not yet exist, cannot be part of the population. A frame cannot exist without a populatio

28、n. Lack of a population and frame makes it impossible to draw a random sample to study a processs behavior.第27頁/共39頁 Models can be used to study these cause-and-effect systems. These models include flowcharts of a process, simulations of the process, and cause-and-effect diagrams. In an analytic stu

29、dy (unlike an enumerative study), there is no underlying statistical theory that enables quantification of uncertainty.第28頁/共39頁 Expert opinion is invaluable in understanding the magnitude of the uncertainty caused by changes to a process. Generally, this uncertainty is best explained by an expert w

30、ho is involved with the process under study.第29頁/共39頁 Improvement or innovation of a process is accomplished using the Plan-Do-Study-Act (PDSA) cycle. The PDSA cycle is used to narrow the difference between process performance and customer (either internal or external) needs and wants. 第30頁/共39頁 The

31、 aim of the PLAN stage is to determine an improvement or innovation to a process that will narrow the difference between process performance and customer needs and wants. (i.e. old flowchart to new flowchart) The DO stage of the PDSA cycle requires that planned experiments be conducted to determine

32、how best to implement the PLAN established in the previous stage. Experiments should be conducted on a small scale, using a laboratory, an office or plant site, or, with his consent, even a customers location. The aim of the STUDY stage is to determine if the PLAN has been effective in decreasing th

33、e difference between process performance and customer needs and wants. In the ACT stage, the PLAN should be integrated into the process.第31頁/共39頁 Errors in Analytic Studies A type one error occurs when action is taken on a process when it should have been left alone. A type two error occurs when we

34、fail to take action on a process when action is appropriate.第32頁/共39頁 Design of Analytic Studies We can increase our degree of belief in a prediction from an analytic study by considering: Building of knowledge in a sequential fashion Testing over a wide range of conditions Selection of units for th

35、e study 第33頁/共39頁 Building of Knowledge in a Sequential Fashion Experiments performed in the iterations of the PDSA cycle, in combination with theory about the process from subject matter experts, may increase the degree of belief in predictions about the future behavior of the process under study.

36、This degree of belief is increased as sequential predictions about the processs future behavior come closer to the actual performance of the process.第34頁/共39頁 Testing over a Wide Range of Conditions The degree of belief in the predictive value of the knowledge gained from an analytic study is increased if the analytic study yields the same results over a wide range of conditions. Only an expert in the subject matter under s