In 2005 Stanley Ahlon and three financial partners formed Dy

In 2005, Stanley Ahlon and three financial partners formed Dynamic Scales, Inc. The company was based on an idea Stanley had for developing a scale to weigh trucks in motion and thus eliminate the need for every truck to stop at weigh stations along highways. This dynamic scale would be placed in the highway approximately one-quarter mile from the regular weigh station. The scale would have a minicomputer that would automatically record truck speed, axle weights, and climate variables, including temperature, wind, and moisture. Stanley Ahlon and his partners believed that state transportation departments in the United States would be the primary market for such a scale. As with many technological advances, developing the dynamic scale has been difficult. When the scale finally proved accurate for trucks traveling 40 miles per hour, it would not perform for trucks traveling at higher speeds. However, eight months ago, Stanley announced that the dynamic scale was ready to be field-tested by the Nebraska State Department of Transportation under a grant from the federal government. Stanley explained to his financial partners, and to Nebraska transportation officials, that the dynamic weight would not exactly equal the static weight (truck weight on a static scale). However, he was sure a statistical relationship between dynamic weight and static weight could be determined, which would make the dynamic scale useful. Nebraska officials, along with people from Dynamic Scales, installed a dynamic scale on a major highway in Nebraska. Each month for six months data were collected for a random sample of trucks weighed on both the dynamic scale and a static scale. Excel sheet presents these data. Once the data were collected, the next step was to determine whether, based on this test, the dynamic scale measurements could be used to predict static weights. A complete report will be submitted to the U.S. government and to Dynamic Scales.

Now, when sketching the relationship between y and all the x’s you will find that the relation is a linear relationship. Then when attempt to do the multiregression analysis, the perfect model will relay only on x1(Front - Axle Dynamic Weight (lb)). But Stanley Ahlon and the three financial partners inc. believed that the value of y (Front - Axle Static Weight (lb)) depends on more than that but the data could not be enough to detect that.

Is there any other way to find a better model that makes y relies on more than one x, if there is can you write the equation of that model?

For the chosen model is there an evidence of multicolinearity? What can make it appear?

Also for the chosen model, analysis the residuals and comment on the results? If you (cannot draw the histogram analysis what you can).

Again for the chosen model, calculate the Axle Statistics weight for a truck with a dynamic weight of 1800 lb traveling 38 miles per hour in a temperature of 21O with a 4% moister.

Front - Axle Static Weight (lb) (y) Front - Axle Dynamic Weight (lb) (x1) Truck speed (mph) (x2) Tempreture (F) (x3) Moistue (%) (x4)
1800 1625 52 21 0
1311 1904 71 17 0.15
1504 1390 48 13 0.4
1388 1402 50 19 0.1
1250 1100 61 24 0
2102 1950 55 26 0.1
1410 1475 58 32 0.2
1000 1013 59 38 0.15
1430 1387 43 24 0
1073 948 59 18 0.4
1502 1493 62 34 0
1721 1902 67 36 0
1113 1415 48 42 0.21
978 983 59 29 0.32
1254 1149 60 48 0
994 1052 58 37 0
1127 999 52 34 0.21
1406 1404 59 40 0.4
875 900 47 48 0
1350 1275 68 51 0
1102 1120 55 52 0
1240 1253 57 57 0
1087 1040 62 63 0
993 1102 59 62 0.1
1408 1400 67 68 0
1420 1404 58 70 0
1808 1790 54 71 0
1401 1396 49 83 0
993 1004 62 88 0.4
1150 1127 64 81 0

Solution

sorry bt refer ur question to advanced maths section.

In 2005, Stanley Ahlon and three financial partners formed Dynamic Scales, Inc. The company was based on an idea Stanley had for developing a scale to weigh tru
In 2005, Stanley Ahlon and three financial partners formed Dynamic Scales, Inc. The company was based on an idea Stanley had for developing a scale to weigh tru

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