A company makes electrical resistors. The perfect resistor has a value of 400 ohms. A sample of 2000 resistors was tested and found to have a mean of 391.5 ohms and a standard deviation of 22.5 ohms. Assuming a normal distribution:a. How many resistors in the sample will have more than 440 ohms of resistance?b. How many resistors in the sample will have less than 360 ohms of resistance?note: you can use the frequency distribution table picture I attached. Areas under the StandardNormal Curve from 0 to zz 00.01.02.03.04.05.06.07.08.090.0.0000.004 0.008.0.012 0.016 0.019 9.023 9.027 9.031 9.035 90.1.039 8.043 3.047 8.051 7.055 7.059 6.063 6 .0675.071 4.075 40.2.079 3.083 2.087 1.091 0 .0948.098 7102 6.106 4.110 3.114 10.3.117 9.121 7.125 5.129 3.133 1.136 8140 6.144 3.148 0.151 70.4 .155 4.159 1.162 8.166 4.170 0.173 6177 2.180 8.184 1.187 90.5.191 5.195 0.198 5.201 9.205 4.208 8.212 3.215 7.219 0.222 40.6.225 8.229 1.232 4.235 7.238 9.242 2.245 4.2486.251 8.254 90.7.258 0.261 2.264 2.267 3.270 4.273 4.276 4.279 4.282 3.285 20.8.288 1.291 0.293 9.296 7.299 6.302 3.305 1.307 8.310 6.313 30.9.315 9.318 6.321 2.323 8.326 4.328 9.331 5.334 0.336 5.338 91.0.341 3.343 8.3461.348 5.350 8.353 1.355 4.357 7.359 9.362 11.1.364 3.366 5.3686.370 8.372 9.374 9.377 0 .3790.381 0 .383 01.2.384 9.386 9.388 8.390 7.392 5.394 4.396 2.398 0.399 7.401 51.3 .403 2.404 9.406 6.408 2.409 9.411 5.413 1.414 7.416 2.417 71.4 .419 2.420 7 .4222.423 6.425 1.426 5.427 9.429 2.430 6 .43191.5.433 2 .4345.435 7.437 0.438 2.439 4.440 6.441 8.442 9.444 11.6.445 2.446 3.447 4.448 4.449 5.450 5.451 5.452 5.453 5.454 51.7.4555.456 4.457 3.458 2.459 1.459 9.460 8.461 6.462 5 .463 31.8.464 1.464 9.465 6.466 4.467 1.467 8.468 6.469 3.469 9.470 61.9.471 3.471 9.472 6.473 2.473 8.474 4.475 0.475 6.476 1.476 72.0 .477 2.477 8 .478 3.478 8.479 3.479 8.480 3 .4808.481 2.481 7

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A company makes electrical resistors. The perfect resistor has a value of 400 ohms. A sample of 2000 resistors was tested and found to have a mean of 391.5 ohms and a standard deviation of 22.5 ohms. Assuming a normal distribution: a. How many resistors in the sample will have more than 440 ohms of resistance? b. How many resistors in the sample will have less than 360 ohms of resistance? note: you can use the frequency distribution table picture I attached.

A company makes electrical resistors. The perfect resistor has a value of 400 ohms. A sample of 2000 resistors was tested and found to have a mean of 391.5 ohms and a standard deviation of 22.5 ohms. Assuming a normal distribution: a. How many resistors in the sample will have more than 440 ohms of resistance? b. How many resistors in the sample will have less than 360 ohms of resistance? note: you can use the frequency distribution table picture I attached.

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Concept explainers

Theory and Design for Mechanical Measurements

Measurement is a term that refers to analyzing a manufactured component regarding the degree of accuracy for dimensions, tolerances, geometric profile, roundness, flatness, smoothness, etc. Measurement always involves comparing the manufactured component or the prototype with a standard specimen whose dimensions and other parameters are assumed to be perfect and do not undergo changes with respect to time.Precisely in mechanical engineering the branch that deals with the application of scientific principles for measurements is known as metrology. The domain of metrology in general deals with various measurements like mechanical, chemical, thermodynamic, physical, and biological measurements. In mechanical engineering, the measurements are limited to mechanical specific such as length, mass, surface profile, flatness, roundness, viscosity, heat transfer, etc.

Basic principles of engineering metrology

Metrology is described as the science of measurement, precision, and accuracy. In other words, it is a method of measurement based on units and predefined standards.

Question

A company makes electrical resistors. The perfect resistor has a value of 400 ohms. A sample of 2000 resistors was tested and found to have a mean of 391.5 ohms and a standard deviation of 22.5 ohms. Assuming a normal distribution:
a. How many resistors in the sample will have more than 440 ohms of resistance?
b. How many resistors in the sample will have less than 360 ohms of resistance?

note: you can use the frequency distribution table picture I attached.

Areas under the Standard
Normal Curve from 0 to z
z 00
.01
.02
.03
.04
.05
.06
.07
.08
.09
0.0
.0000
.004 0
.008.0
.012 0
.016 0
.019 9
.023 9
.027 9
.031 9
.035 9
0.1
.039 8
.043 3
.047 8
.051 7
.055 7
.059 6
.063 6 .0675
.071 4
.075 4
0.2
.079 3
.083 2
.087 1
.091 0 .0948
.098 7
102 6
.106 4
.110 3
.114 1
0.3
.117 9
.121 7
.125 5
.129 3
.133 1
.136 8
140 6
.144 3
.148 0
.151 7
0.4 .155 4
.159 1
.162 8
.166 4
.170 0
.173 6
177 2
.180 8
.184 1
.187 9
0.5
.191 5
.195 0
.198 5
.201 9
.205 4
.208 8
.212 3
.215 7
.219 0
.222 4
0.6
.225 8
.229 1
.232 4
.235 7
.238 9
.242 2
.245 4
.2486
.251 8
.254 9
0.7
.258 0
.261 2
.264 2
.267 3
.270 4
.273 4
.276 4
.279 4
.282 3
.285 2
0.8
.288 1
.291 0
.293 9
.296 7
.299 6
.302 3
.305 1
.307 8
.310 6
.313 3
0.9
.315 9
.318 6
.321 2
.323 8
.326 4
.328 9
.331 5
.334 0
.336 5
.338 9
1.0
.341 3
.343 8
.3461
.348 5
.350 8
.353 1
.355 4
.357 7
.359 9
.362 1
1.1
.364 3
.366 5
.3686
.370 8
.372 9
.374 9
.377 0 .3790
.381 0 .383 0
1.2
.384 9
.386 9
.388 8
.390 7
.392 5
.394 4
.396 2
.398 0
.399 7
.401 5
1.3 .403 2
.404 9
.406 6
.408 2
.409 9
.411 5
.413 1
.414 7
.416 2
.417 7
1.4 .419 2
.420 7 .4222
.423 6
.425 1
.426 5
.427 9
.429 2
.430 6 .4319
1.5
.433 2 .4345
.435 7
.437 0
.438 2
.439 4
.440 6
.441 8
.442 9
.444 1
1.6
.445 2
.446 3
.447 4
.448 4
.449 5
.450 5
.451 5
.452 5
.453 5
.454 5
1.7
.4555
.456 4
.457 3
.458 2
.459 1
.459 9
.460 8
.461 6
.462 5 .463 3
1.8
.464 1
.464 9
.465 6
.466 4
.467 1
.467 8
.468 6
.469 3
.469 9
.470 6
1.9
.471 3
.471 9
.472 6
.473 2
.473 8
.474 4
.475 0
.475 6
.476 1
.476 7
2.0 .477 2
.477 8 .478 3
.478 8
.479 3
.479 8
.480 3 .4808
.481 2
.481 7

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