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【正文】 shown here. We can see from the PValue of .263 that again we would fail to reject the null hypothesis. Note that the F test assumes normality ?Note that we get a graphical summary of both sets of data as well as the relevant statistics…. Analyzing the data…. ?Levene’s test also pares the variance of the two samples and is robust to nonnormal data. Again, the PValue of .229 indicates that we would fail to reject the null hypothesis. ?Here we have box plot representations of both populations. 169。The National Graduate School of Quality Management ? 94 Paired Comparison ?Go to Stat…. ?Basic Statistics… ? Paired t….. 169。The National Graduate School of Quality Management ? 102 Note that you will have the critical population and test statistics displayed in the session window. ?Minitab builds the table for you. Note that our original data is presented and directly below, Minitab calculates the expected values. ?Here, Minitab calculates the Chi Square statistic for each data point and totals the result. The calculated Chi Square statistic for this problem is . Performing the Analysis…. 169。The National Graduate School of Quality Management ? 110 Main Effects Select ?C4 Response ?C5 Factors ?OK 169。The National Graduate School of Quality Management ? 118 Bowling Example (continued) Remove the option to Randomize Runs…. Now, select OK and go back to the main screen. Once at the main screen select OK... 169。The National Graduate School of Quality Management ? 126 Bowling Example (continued) ?Select Main Effects Plot and then Setup… 169。The National Graduate School of Quality Management ? 132 Bowling Example (continued) ?The more the lines diverge from being parallel, the more the interaction. ?We see that the strongest interaction (still not significant) is between the lane and the ball. ?We know from our earlier analysis that none of。The National Graduate School of Quality Management ? 124 Bowling Example (continued) Note that only one effect has a significance greater than 95%. All the remaining factors and interactions are not statistically significant. 169。The National Graduate School of Quality Management ? 116 Bowling Example (continued) Select your design…. We will be using the Full (Factorial) and again we can see that it will require 8 runs… Now, select OK and go back to the main screen. Once at the main screen select Factors... 169。The National Graduate School of Quality Management ? 108 Note that the P value is less than .05 that means that we reject the null hypothesis Analyzing the results…. 169。The National Graduate School of Quality Management ? 100 Let’s set up a contingency table…. ?Contingency tables are found under Stat…. Tables… Chi Square Test…. 169。The National Graduate School of Quality Management ? 92 Paired Comparisons ? In paired parisons we are trying to “pair” observations or treatments. An example would be to test automatic blood pressure cuffs and a nurse measuring the blood pressure on the same patient using a manual instrument. ? It can also be used in measurement system studies to determine if operators are getting the same mean value across the same set of samples. ? Let’s look at an example: 169。The National Graduate School of Quality Management ? 84 ?Now that we have our data stacked, we are ready to test for equal variances.… ?Go to Stat… ANOVA…. Test for equal Variances... Checking for equal variance.. 169。The National Graduate School of Quality Management ? 76 Note that the data does not fit the normal curve very well... Note that the Long Term capability (Ppk) is . This equates to a Z value of 3*= standard deviations or sigma values. This equates to an expected defect rate PPM of 147,055. INTERPRETING THE DATA…. 169。The National Graduate School of Quality Management ? 68 Scatter plot.... ?There is another way we can generate these scatter plots…. ?Go to: ?Graph… ?Matrix Plot... 169。The National Graduate School of Quality Management ? 60 Boxplot.... Fill out the screen as follows: ?Select “filler 1” for our Y Variable…. ?Select “head” for our X Variable…. ?Select OK….. 169。The National Graduate School of Quality Management ? 52 Histogram.... Fill out the screen as follows: ?Select filler 1 for the Y Variable…. ?Select head for the X Variable ?Select OK….. 169。The National Graduate School of Quality Management ? 44 Histogram.... Fill out the screen as follows: ?Select GPA for our X value Graph Variable ?Hit OK….. 169。The National Graduate School of Quality Management ? 36 Presenting the results.... ?Now all we need to do is tune the presentation….. ?Here we position the graph and summary and put in the appropriate takeaway... ?Then we are ready to present…. 169。The National Graduate School of Quality Management ? 28 Use Minitab to do the Analysis... ?Minitab now does the analysis and presents the results... ?Note that in this case there is a graph and an analysis summary in the Session Window… ?Let’s say we want to use both in our PowerPoint presentation…. 169。The National Graduate School of Quality Management ? 20 Starting with Excel... Load file “Sample 1” in Excel…. 169。The National Graduate School of Quality Management ? 12 Menu Bar Graph Menu Key Functions ?Data Plotting Capabilities ?Scatter Plot ?Trend Plot ?Box Plot ?Contour/3 D plotting ?Dot Plots ?Probability Plots ?Stem Leaf Plots 169。The National Graduate School of Quality Management ? 4 Text Column C1T (Designated by T) Numeric Column C3 (No Additional Designation) Data Window Column Conve
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