I think you are asking whether weight is correlated with crash rating. You initial answer was no. this bothers you? You think that large vehicles should be safer than little ones?
Why does "should" trump "observed."? But to proceed. You are searching to find a pattern in the data. This is good - keep looking. As for grouping the data into subgroups by weight, then looking to see if perhaps this approach will give you a correlation that you couldn't 'see' before - watch out! When you group data into subgroups on the weight axis, you are giving away information. All the weights between 1500 and 2000 will be crammed together to provide one average rating (and a stdev, don't forget:). If there is a correlation between weight and rating, we should expect a small difference between the 1500 and 2000 lb. car. You have turned this small difference into an error term (into that stdev). I predict the sub grouping will not reveal a strong correlation that did not exist before. Maybe crash ratings are not related to vehicle mass? Maybe crash survival is not related to crash ratings? I know (freshman physics) that when a little vehicle strikes a large one, the passengers in the small one experience much more change in velocity (acceleration, which relates to force applied, which relates to damage to the body). Do the little ones experience as many crashes, or do they practice emergency avoidance better? disclaimer: As the owner of a nominally small car under 2200 lbs. (1 metric ton), I have a personal interest in your results. Please share it with us when you conclude. Cheers, Jay Serge wrote: > Hello, > > I have to do a final project for my Statistics class. I chose to do a > project on the relationship between a car's weight and its 4 crash > test ratings (2 front for passenger and driver and 2 side for front > and rear). The ratings are 1 - 5 (the number of stars); the higher the > rating, the safer the car. I got all my data from crashtest.com. In > all, I got data for 187 cars - that is, the weight and the 4 ratings. > However, when > I did a scatterplot of any 1 of the front ratings vs. weight the r > coefficient was very close to 0 and the plot did not show a pattern. > When I plotted the side ratings vs. weight, r was about .6 in both > cases (a mild relationship). Thus, I can't really conclude anything > from this. What I am thinking of doing and what I am asking about is > this: If I separate my data into 9 groups based on weight where each > group spans 500 pounds so that group1 has cars with weights 1501 - > 2000 and group > 9 has 5501 - 6000 and then take the mean of all 4 ratings in each of > these groups and plot them against the mean weight in each group for > all 4 ratings (again, 4 separate plots), will I get a more definite > relationship (I haven't done it yet so I don't know) and even more > importantly, will this apparent relationship be statistically > significant and why or why not (why does grouping help or why not)? If > not, can you suggest something else that I may be able to do. Thanks > so much for your help. > > 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/ . > ================================================================= -- Jay Warner Principal Scientist Warner Consulting, Inc. 4444 North Green Bay Road Racine, WI 53404-1216 USA Ph: (262) 634-9100 FAX: (262) 681-1133 email: [EMAIL PROTECTED] web: http://www.a2q.com The A2Q Method (tm) -- What do you want to improve today? . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
