Hello, I am posting to report my results and to thank those that have helped with this. Thanks again! Basically, I grouped the data into 9 different weight groups as I described previously. I then thew out groups 1, 8, and 9 because there wasn't enough data in each group for the mean to be truly representative of the population of all cars in that weight group (ex. group 9 had only 2 cars). I then plotted weight group (x) vs each of the 4 ratings (y). I found that there was a very strong positive linear relationship between weight group and each of the side ratings (in each case, r was > .95). Using a hypothesis test I showed that this was significant with respect to the population. However, the realtionship between weight group and the front ratings did not seem to be linear. In part, this is because front tests are conducted by crashing the car against the wall and thus, the ratings should be compared in exactly that sense ... not in the sense of a car crashing head on with an "average weight car." For my sample (187 cars), the pattern was well fitted by a concave down parabola (ax^2 + bx + c; with a<0). The critical point was above and between groups 3 and 4. I used Maple to get two specific equations. The equation fit the points for the 6 groups very well for the front driver rating. The fit was ok but not as good for the front passenger rating. I then wanted to see if there was signifcant evidence that imported cars (non-US) were safer than domestic cars in each of the 4 crash types. I split the data and found the mean rating for each type for imported and domestic. Each imported mean score turned out to be higher. I performed 4 significance tests and all 4 showed that the difference was significant with respect to the population. Thus, my study seemed to favor heavier imported cars. I welcome any questions or comments.
Cheers, Serge . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
