In an effort to overcome the noise problem presented by his company’s impact tools (recall that μ = 89 dB) the manufacturer’s sale representative Art Snakeoil now suggests replacing the old line of noisy impact tools with his new line of quieter pistol grip impulse tools. Unfortunately, he does not have many samples to provide for testing. Nine tools are tested with the following data provided as follows (in units of dB): 85.1, 90.1, 86.3, 85.4, 89.3, 88.4, 86.3, 89.4, and 86.2.
The Purchasing Department now asks the Engineering Department to determine if the sound level of the pulse tool samples is significantly reduced from that of the impact tools presently being used.
The Engineering Department, using a significance level of α = 0.01 analyzes the noise level of the sample of nine tools by following the format:
a. State the appropriate hypothesis
b. Test the hypothesis, using α = 0.01
c. Construct a 99% confidence interval on the tool noise level.
1. H_{0}: μ = 89
2. H_{a}: μ < 89
3. α = 0.01 (level of significance)
4. n is small (n < 30, n = 9)
5. σ is unknown ⇒ use the t test
6. n = 9
7. From the sample data, we find
S = 1.91
From Table 4.3 for α = 0.01, n = 9, we obtain
∂ = n − 1 = 8
and
t_{0.01,8} = 2.896Also we find
t_{0}=\frac{\overline{x}-\mu _{0} }{S/\sqrt{n} } =\frac{87.39-89}{1.91/\sqrt{9} } =-2.53Displaying this data on a sketch reveals
Hence, since the value of −2.53 lies within the bounds of −2.896, we accept H_{0}, and therefore reject H_{A} which indicates that the new (albeit small) sample of tools, at a significance level of 0.01, is statistically similar to the original noisy tools with respect to noise. Evaluating the same problem by examining its L.L. yields:
LL=\mu _{0}-t_{0.01,8}\frac{S}{\sqrt{n} }=89-2.896\frac{\left(1.91\right) }{\sqrt{9} } \\LL=87.16Displaying the data on a sketch yields
8. Since \overline{x} = 87.39 > LL = 87.16
Accept H_{0}: μ = 89
Reject H_{0}: μ < 89
We conclude, therefore, that the means of the population from which the nine samples were randomly taken (i.e., the pulse tool samples) will have no improvement in the noise attenuation and is therefore no different or better statistically than the noise level of the original population of noisy impact tools.
TABLE 4.3 | ||||||||
Percentile Values for Student’s t Distribution [5] | ||||||||
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1 | 0.325 | 0.727 | 1.376 | 3.078 | 6.314 | 12.706 | 31.821 | 63.657 |
2 | 0.289 | 0.617 | 1.061 | 1.886 | 2.92 | 4.303 | 6.965 | 9.925 |
3 | 0.277 | 0.584 | 0.978 | 1.648 | 2.353 | 3.182 | 4.541 | 5.841 |
4 | 0.271 | 0.569 | 0.941 | 1.533 | 2.132 | 2.776 | 3.747 | 4.604 |
5 | 0.267 | 0.559 | 0.920 | 1.476 | 2.015 | 2.571 | 3.365 | 4.032 |
6 | 0.265 | 0.553 | 0.906 | 1.440 | 1.943 | 2.447 | 3.143 | 3.707 |
7 | 0.263 | 0.549 | 0.896 | 1.415 | 1.895 | 2.365 | 2.998 | 3.499 |
8 | 0.262 | 0.546 | 0.889 | 1.397 | 1.860 | 2.306 | 2.896 | 3.355 |
9 | 0.261 | 0.543 | 0.883 | 1.383 | 1.833 | 2.262 | 2.821 | 3.250 |
10 | 0.260 | 0.542 | 0.879 | 1.372 | 1.812 | 2.228 | 2.764 | 3.169 |
11 | 0.260 | 0.540 | 0.876 | 1.363 | 1.796 | 2.201 | 2.718 | 3.106 |
12 | 0.259 | 0.539 | 0.873 | 1.356 | 1.782 | 2.179 | 2.681 | 3.055 |
13 | 0.259 | 0.538 | 0.870 | 1.350 | 1.771 | 2.160 | 2.650 | 3.012 |
14 | 0.258 | 0.537 | 0.868 | 1.345 | 1.761 | 2.145 | 2.624 | 2.977 |
15 | 0.258 | 0.536 | 0.866 | 1.341 | 1.753 | 2.131 | 2.602 | 2.947 |
16 | 0.258 | 0.535 | 0.865 | 1.337 | 1.746 | 2.120 | 2.583 | 2.921 |
17 | 0.257 | 0.534 | 0.863 | 1.333 | 1.74 | 2.110 | 2.567 | 2.898 |
18 | 0.257 | 0.534 | 0.862 | 1.330 | 1.734 | 2.101 | 2.552 | 2.878 |
19 | 0.257 | 0.533 | 0.861 | 1.328 | 1.729 | 2.093 | 2.539 | 2.861 |
20 | 0.257 | 0.533 | 0.860 | 1.325 | 1.725 | 2.086 | 2.528 | 2.845 |
21 | 0.257 | 0.532 | 0.859 | 1.323 | 1.721 | 2.080 | 2.518 | 2.831 |
22 | 0.256 | 0.532 | 0.858 | 1.321 | 1.717 | 2.074 | 2.508 | 2.819 |
23 | 0.256 | 0.532 | 0.858 | 1.319 | 1.714 | 2.069 | 2.500 | 2.807 |
24 | 0.256 | 0.531 | 0.857 | 1.318 | 1.711 | 2.064 | 2.492 | 2.797 |
25 | 0.256 | 0.531 | 0.856 | 1.316 | 1.708 | 2.060 | 2.485 | 2.787 |
26 | 0.256 | 0.531 | 0.856 | 1.315 | 1.706 | 2.056 | 2.479 | 2.779 |
27 | 0.256 | 0.531 | 0.855 | 1.314 | 1.703 | 2.052 | 2.473 | 2.771 |
28 | 0.256 | 0.530 | 0.855 | 1.313 | 1.701 | 2.048 | 2.467 | 2.763 |
29 | 0.256 | 0.530 | 0.854 | 1.311 | 1.699 | 2.045 | 2.462 | 2.756 |
30 | 0.256 | 0.530 | 0.854 | 1.310 | 1.697 | 2.042 | 2.457 | 2.75 |
40 | 0.255 | 0.529 | 0.851 | 1.303 | 1.684 | 2.021 | 2.423 | 2.704 |
60 | 0.254 | 0.527 | 0.848 | 1.296 | 1.671 | 2.000 | 2.39 | 2.66 |
120 | 0.254 | 0.526 | 0.845 | 1.289 | 1.658 | 1.980 | 2.358 | 2.617 |
∞ | 0.253 | 0.524 | 0.842 | 1.282 | 1.645 | 1.960 | 2.326 | 2.576 |