1)
Here, I have prepared X bar chart for the above data, I have used Minitab to construct such graph or chart, step- go to Stat> Control Charts> Variable charts for subgroups> X Bar Charts,
Here, we will select the available mean values as applicable for 26 samples, we will get the below graph:
based on below chart and using three sigma quality, UCL value is 4.294 and LCL value is 3.418
2)
Test Results for Xbar Chart of Mean
TEST 7. 15 points within 1 standard deviation of center line
(above and below CL).
Test Failed at points: 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26
as, we have faced continuous up and down of the data
as, we have seen that there are assignable causes, so, we could conclude that process data are NOT in statistical control.
plz dont use hand write. thx!! 15 17 (c) The time needed for checking in at...
4 The time needed for checking in at a hotel is to be investigated. Historically, the process has had a standard deviation equal to 0.146. The means of 26 samples of n=14 are shown below. Sample Mean Sample Mean 1 3.86 14 3.81 2 3.90 15 3.83 3 3.83 16 3.86 4 3.81 17 3.82 5 3.84 18 3.86 6 3.83 19 3.84 7 3.87 20 3.87 8 3.88 21 3.84 9 3.84 22 3.92 10 3.80 23 3.89 11...
The time needed for checking in at a hotel is to be investigated. Historically, the process has had a standard deviation equal to .146. The means of 39 samples of n = 20 are Sample Mean Sample Mean Sample Mean Sample Mean 1 3.86 11 3.88 21 3.84 31 3.88 2 3.90 12 3.86 22 3.82 32 3.76 3 3.83 13 3.88 23 3.89 33 3.83 4 3.81 14 3.81 24 3.86 34 3.77 5 ...
1. Two manufacturing processes are being compared to try to reduce the number of defective products made. During 8 shifts for each process, the following results were observed: Line A Line B n 181 | 187 Based on a 5% significance level, did line B have a larger average than line A? *Use the tables I gave you in the handouts for the critical values *Use the appropriate test statistic value, NOT the p-value method *Use and show the 5...
Gain (V/V) R Setting Totals Averages Sample 1 Sample 2 Sample 3 4 ап 7.8 8.1 7.9 3 5.2 6.0 4.3 = 359.3 i=1 j=1 2 4.4 6.9 3.8 1 2.0 1.7 0.8 This is actual data from one of Joe Tritschler's audio engineering experiments. Use Analysis of Variance (ANOVA) to test the null hypothesis that the treatment means are equal at the a = 0.05 level of significance. Fill in the ANOVA table. Source of Variation Sum of Squares...
Gain (V/V) R Setting Totals Averages Sample 1 Sample 2 Sample 3 4 ап 7.8 8.1 7.9 3 5.2 6.0 4.3 = 359.3 i=1 j=1 2 4.4 6.9 3.8 1 2.0 1.7 0.8 This is actual data from one of Joe Tritschler's audio engineering experiments. Use Analysis of Variance (ANOVA) to test the null hypothesis that the treatment means are equal at the a = 0.05 level of significance. Fill in the ANOVA table. Source of Variation Sum of Squares...